master thesis: virtual communities as a vehicle for science-based external knowledge sourcing e...

Virtual communities as a vehicle for science-based external knowledge sourcing

Cand merc. (MIB) Management of Innovation and Business Development Copenhagen Business School

Academic advisor: Finn Valentin, Dep. of Innovation and Organizational Economics

113 Pages + Appendix STU count: 271.249

2011-11

Dan Herlin 070184-2901

Benedikta Hedegaard-Knudsen 231283-1778

Abstract Over the past decade the world has witnessed a dramatic development of information and

communication technologies (ICT), and one of the most profound manifestations of online

communication is that of virtual communities (VCs). VCs are proliferating across the Internet in

various forms, and companies have become increasingly interested in utilizing VCs as a tool for

external knowledge sourcing and innovation. In the literature, we find that most work on this

topic predominantly relates to market-‐focused crowdsourcing through user-‐ or challenge-‐driven

VCs. In this light, this paper aims to investigate the benefits that a research-‐based VC holds for

science-‐based R&D intensive firms in acting as a vehicle for unguided search of scientific

opportunities, as to ultimately enhance their innovative capacity. Our research takes point of

departure in the combinatorial view of innovation where we recognize that external sources of

knowledge hold great potential for innovating firms. We take an exploratory and multi-‐

disciplinary approach where we combine literature of cognitive economics, sociology,

innovation, ambidexterity and network theory. Moreover, we conduct a prospective single-‐case

study of Novozymes (NZ) -‐ a leading biotechnology firm in the industrial enzyme business. Here,

we assess NZ’ R&D organisation and its current innovation model to conclude that NZ is to

certain extent is trapped in sub-‐optimal routinized exploitative R&D strategies. While NZ’

current innovation model has proved highly efficient in the past, looming challenges in the

enzyme market places Novozymes in a position to benefit from more explorative R&D strategies.

We identify a set of enabling properties that makes virtual communities particularly conducive

for overcoming a number of barriers found in real life (IRL) communities. More specifically, we

highlight how VCs can overcome barriers of time and geographical proximity as well as barriers

of cognitive-‐, disciplinary-‐ and organizational separation. We conclude that VCs hold potential to

act as a brokerage mechanism for bridging structural holes and facilitate external knowledge

sourcing, and ultimately make out a keystone in the development of ambidextrous

organisational capabilities. As a result, we suggest that NZ can engage in more explorative R&D

strategies by means of a VC set-‐up, without compromising the efficient model if innovation

currently in place in the organization.

Copenhagen Business School Master Thesis, Fall 2011 M.Sc. Innovation and Business Development Benedikta Hedegaard-‐Knudsen & Dan Herlin

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Table of Contents List of Abbreviations ...................................................................................................................................................... 3

1. INTRODUCTION .......................................................................................................................................... 5 1.1. PROBLEM STATEMENT .............................................................................................................................................. 8 1.2. CLARIFICATION OF RESEARCH .................................................................................................................................. 8 1.3. DEMARCATION ............................................................................................................................................................ 9 1.4. MOTIVATION ............................................................................................................................................................ 10 1.5 RELEVANCE ................................................................................................................................................................ 10 1.6. DISPOSITION ............................................................................................................................................................. 11

2. METHODOLOGY ....................................................................................................................................... 12 2.1. RESEARCH STRATEGY AND DESIGN ..................................................................................................................... 12 2.2. DATA COLLECTION .................................................................................................................................................. 14 2.2.1. Qualitative research methods .................................................................................................................... 14 2.2.2. Method of verification ................................................................................................................................... 17 2.2.3. Quantitative research method ................................................................................................................... 18

2.3. CRITIQUE OF METHODOLOGY ................................................................................................................................ 18 2.3.2. Limitations ......................................................................................................................................................... 18 2.3.3. Reliability ............................................................................................................................................................ 20 2.3.4. Validity ................................................................................................................................................................. 20 2.3.5. Generalizability ................................................................................................................................................ 21

2.4 DELIMITATIONS ........................................................................................................................................................ 21 2.5. CENTRAL CONCEPTS ............................................................................................................................................... 22

3. LITERATURE REVIEW ............................................................................................................................ 24 3.1. COGNITIVE ECONOMICS .......................................................................................................................................... 25 3.2. BRIEF HISTORY OF ICT AND THE INTERNET ...................................................................................................... 26 3.3. VIRTUAL COMMUNITIES ......................................................................................................................................... 27 3.4. A TYPOLOGY OF VIRTUAL COMMUNITIES FOR EXTERNAL KNOWLEDGE SOURCING ..................................... 29 3.4.1. User-‐driven community ................................................................................................................................ 30 3.4.2. Challenged-‐Based Community ................................................................................................................... 31 3.4.3. Research-‐based community ........................................................................................................................ 31

3.5. RESEARCH GAP ........................................................................................................................................................ 32 4. THEORETICAL DISCUSSION .................................................................................................................. 33 4.1. COMBINATORIAL INNOVATION ............................................................................................................................. 33 4.1.1. The linear-‐ and the chain-‐linked model -‐ The role of science and innovations .................... 35 4.1.2. Exploitation and Exploration ..................................................................................................................... 39 4.1.3. The Ambidexterity Hypothesis ................................................................................................................... 40 4.1.4. Combinatorial Innovation: Models and application of theory .................................................... 41

4.2 NETWORKS, KNOWLEDGE AND STRUCTURAL HOLES ........................................................................................ 45 4.2.1. The Social Structure of Networks ............................................................................................................. 46 4.2.2. Structural Holes ............................................................................................................................................... 48 4.2.3. Structural holes and opportunities in segmented networks ........................................................ 49 4.2.4. Brokerage and Innovation .......................................................................................................................... 50 4.2.5. Cognitive Distance ........................................................................................................................................... 51 4.2.6. Social Capital and Innovation .................................................................................................................... 52

4.3. VIRTUAL COMMUNITIES AND KNOWLEDGE SOURCING .................................................................................... 54 4.3.1. Knowledge Sharing and Information Exchange in ‘virtual worlds’ .......................................... 54

4.4. THEORETICAL SYNTHESIS AND APPLICATION .................................................................................................... 55 5. NOVOZYMES -‐ CASE COMPANY PROFILE .......................................................................................... 58 5.1. NOVOZYMES R&D ORGANIZATION ....................................................................................................................... 59


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5.2. LOOMING CHALLENGES .......................................................................................................................................... 61 6. ANALYSIS .................................................................................................................................................... 62 6.1. PART I -‐ NOVOZYMES’ INNOVATION MODEL ....................................................................................................... 63 6.1.1. R&D in transition at Novozymes ............................................................................................................... 64 6.1.2. Novozymes’ innovation model ................................................................................................................... 66 6.1.3. R&D at Novozymes: basic vs. applied scientific research ............................................................... 68 6.1.4. R&D project groups at Novozymes .......................................................................................................... 69 6.1.5. Novozymes and The Long Tail of R&D ................................................................................................... 71 6.1.6. The emergence of revolutionising technologies for enzyme research ..................................... 73 6.1.7. Conclusion: analysis part I ........................................................................................................................... 75

6.2 ANALYSIS PART II – VIRTUAL INNOVATION BROKER ....................................................................................... 76 6.2.1. A great place to start ..................................................................................................................................... 76 6.2.2. Structural holes and combinatorial innovation ................................................................................. 77 6.2.3. The Virtual Innovation Broker .................................................................................................................. 78 6.2.4 Enabling and inhibiting properties of virtual communities .......................................................... 80 6.2.5. Trends in community life online ................................................................................................................ 83 6.2.6. Conclusion: analysis part II ......................................................................................................................... 86

6.3 ANALYSIS PART III – THE AMBIDEXTROUS INNOVATION MODEL .................................................................. 87 6.3.1. Optimal Scope Continuum ........................................................................................................................... 87 6.3.2. Overcoming obstacles to ambidexterity ................................................................................................ 90 6.3.3. Ambidextrous innovation ............................................................................................................................. 93 6.3.4. Conclusion: analysis part III ....................................................................................................................... 95

6.4. CONCLUSION: ANALYSIS PART I, II, II .................................................................................................................. 96 7. DISCUSSION OF FINDINGS AND FUTURE PERSPECTIVES ........................................................... 99 8. BIBLIOGRAPHY ..................................................................................................................................... 105 8.1. BOOKS AND ARTICLES ......................................................................................................................................... 105 8.2. ONLINE SOURCES .................................................................................................................................................. 113

9. APPENDIX ................................................................................................................................................ 114 APPENDIX 1: INTERVIEW SUMMARY ......................................................................................................................... 115 APPENDIX 2: ONLINE QUESTIONNAIRE SUMMARY ................................................................................................. 146 APPENDIX 3: NOVOZYMES SALES DATA AND GLOBAL ENZYME MARKET ............................................................ 151 APPENDIX 4: ONLINE TRENDS – EMERGING SCIENTIFIC COMMUNITIES ............................................................. 153 APPENDIX 5: ENABLING AND INHIBITING PROPERTIES OF A VIRTUAL COMMUNITY ........................................ 159


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List of Abbreviations

B-‐2-‐B Business to Business

B-‐2-‐C Business to Consumer

FtF Face to Face

ICT Information and Communication Technology

IRL In Real Life

LM Linear Model of Innovation

NZ Novozymes

R&D Research and Development

VC Virtual Community

VIB Virtual Innovation Broker


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“The value of an idea lies not its origin, but in its delivery”

-‐ Ronald Burt, 2001


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1. Introduction Do you have a good idea? A sudden spark of inspiration? A memory? Where did it come

from? We are often led to believe that ideas pop out of nowhere. Famous tales suggest

that great ideas are the result of epiphanies, such as Archimedes who supposedly while

lying comfortably in his bathtub suddenly realized that ‘any object, wholly or partially

immersed in a fluid, is buoyed up by a force equal to the weight of the fluid displaced by

the object’1; or of Isaac Newton who, when the apple fell from the tree, suddenly grasped

that the ‘…gravitational force is proportional to the product of the two masses

and inversely proportional to the square of the distance between them’2. In the light of

the notion of combinatorial innovation, the ‘Eureka!’ moment metaphor and Edison’s

light bulb allegory are reduced to romanticized versions of the truth. The point is that

most great ideas have a historical record, and first see the day of light after being

processed iteratively by a number of actors; often as result of collective effort of

‘connecting the dots’ (Burt, 2001). Similarly, innovations emerge through the

recombination of the technological components and processes that lie along the

contemporary technology frontier (Fleming & Sorensen, 2004). Through collaboration

and connectivity, the combination of pools of knowledge in due course leads up to a

moment of breakthrough.

The traditional view of creative processes, is that these are the result of a genetic

precondition or personal trait, but creativity is an import-‐export game -‐ not a creation

game (Burt, 2004). Hence, “the value in an idea lies not in its origin, but in its delivery” (Ibid.:1).

But how can the delivery of ideas be facilitated? It becomes important to understand

what circumstances that are required to facilitate the emergence of ideas? Behavioural

sciences holds part of the answer. A generic notion from sociology is that information

circulates more within groups of people than across groups of people (Lin et al., 2001).

With the notion of combinatorial innovation in mind, many scholars suggest that multi-‐

disciplinarity opens up for novel and more radical combinations. Nevertheless, since the

composition of groups often takes a homogenous character, it has been proved

challenging to reach out to actors who reside in distant networks and disciplines. What

1 Archimedes discoveries in the bath: http://www.mlahanas.de/Greeks/ArchimedesBath.htm 2 How Newton Built on Galileo Ideas: http://galileo.phys.virginia.edu/classes/109N/lectures/newtongl


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could possibly incentivize people who do not naturally come together, to meet and share

knowledge and experiences?

Over time the mechanisms or ‘enabling spaces’ for connecting and facilitating

collaboration and mediation of information across people have taken many forms. In the

Age of Enlightment3, enabling spaces took the form of coffee houses. According to Cowan

“…the coffeehouse was a place for individuals to congregate, to read, as well as to learn

from, and debate with each other” (2005:89). Over the years more sophisticated enabling

spaces have emerged, such as schools and universities, and today’s counterpart of the

coffeehouses during the Enlightment is indisputably the Internet. Human social

interaction has changed dramatically over the past decade, much as a result of

developments in communication technology and the emergence of the Internet. The

central utility of the Internet is to facilitate connectivity and the notion of ‘sharing’ is the

substance of online interaction. The applications of the Internet found in in human life

today are countless. Social and public life is increasingly mediated through Internet

technology, essentially reframing our everyday experiences and changing the very fabric

of society. Since the emergence of the Internet in the late 1990’s, it has brought about

profound impacts on the world economy, on politics, on culture and social progress, and

promoted the transformation of social production and information dissemination

(Xinhua, 2010). The proliferation of low cost access to the Internet has made way for

new means by which inter-‐organizational and inter-‐personal interaction can take place,

allowing connections to be made and networks to be built, earlier unimaginable.

Essentially it has grown to become an integrated facet of life for people, organizations

and businesses -‐ a given piece of our information and communication landscape -‐ and

not the least a major source and catalyst for innovation.

One of the most profound manifestations of online communication technology is that of

virtual communities (VC). The mode for online communication has moved from

monologue to dialogue, i.e. from ‘one-‐to-‐many’ to ‘many-‐to-‐many’ (Brandtzæg et al.,

2010). VCs have soured in numbers over the past decade, and online ‘connections’ are

multiplying at a phenomenal rate. Today, the multiplicity of VCs is growing from broad

to narrow in scope and VCs are to be found within almost any area of interest, industry

3 Timespan: 1650-1796 (Frost, 2011)


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or field of study. A VC can establish linkages and facilitate interaction between

geographically dispersed actors, and act as a vehicle for information exchange and

knowledge sharing (Füller et al., 2004). The interest for how online communication

technologies can accommodate new knowledge creation and enhance innovation is

growing among companies (Brandtzæg et al., 2010).

One such company is Novozymes (NZ) -‐ a Danish biotechnology firm and world leader in

industrial enzymes. The business of industrial enzymes is highly R&D-‐intensive, and

16% of NZ’ workforce is employed in R&D, and about 14% of revenue is re-‐invested in

research (Annual Report, 2010). The constant search for new knowledge is an integral

part of NZ’ business agenda, and the R&D organization is always seeking new leads for

application areas of its enzyme technologies. Along with developments of information

and communication technologies (ICT), the R&D organization at NZ has turned their

interest towards opportunities that can be realized by means of external knowledge

sourcing through the use of virtual community technologies. More specifically, they have

asked us to investigate to what extent a virtual community can help facilitate efficient

external knowledge sourcing and make R&D activities more explorative.

Innovating firms are said to face two conflicting processes of organizational learning:

exploration and exploitation. Exploitation deals with static efficiency and relates to

refinement of existing products and procedures and incremental innovation, whereas

exploration relates to dynamic efficiency and involves search for new options in distant

fields and more radical innovation (March, 1991). We know that managing the scope of

exploration and exploitation comprise a paradoxical challenge, and to do so successfully

is said to require ambidextrous organizational capabilities (Tushman & O’Reilly, 1996).

We draw upon the notion of ambidexterity and seek to understand the extent to which a

VC can support an ambidextrous model of innovation to emerge, as we seek to uncover

potential opportunities that can be realized by leveraging particular qualities of VCs to

help manage exploitation and exploration simultaneously.


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1.1. Problem Statement In this thesis we explore the following research question: How can a virtual community

facilitate external knowledge sourcing so as to enhance the innovative capacity of

Novozymes’ R&D organization?

In this effort, we conduct a three-‐pronged analysis in which the three below sub-‐

questions are explored, respectively:

Q1: To what extent is the current innovation model at Novozymes conducive for

effective external knowledge sourcing?

Q2: How can virtual communities support the facilitation of external knowledge

sourcing for science-‐based firms?

Q3: Can a virtual community make way for an ambidextrous innovation model?

1.2. Clarification of research Q1: The first sub-‐question serves to address the extent to which the current innovation

model at NZ is conducive for external knowledge sourcing. Here we analyse NZ’ the

scope of R&D activities and its current innovation model. We investigate the

characteristics of the enzyme research environment at NZ and develop arguments for

why distant search is deemed a critical element in the development of novel and

revolutionary applications in enzyme technology. Ultimately we conclude that NZ

suffers from a local search bias and indeed hold to benefit from external knowledge

sourcing.

Q2: Secondly, mechanisms for external knowledge sourcing are reviewed, where we

take a particular interest in the role of virtual communities for facilitating external

knowledge sourcing. Here, existing literature and case-‐examples of virtual communities

are revised, and a set of enabling properties for how virtual communities can act as a

vehicle for external knowledge sourcing is identified. We further expand the second part

of the analysis and take pragmatic approach. Here we highlight a number of trends in

online community life as well conduct an online survey, where we find supporting

arguments for VCs in research-‐based environments.

Q3: Thirdly, we explore the notion of cognitive distance and explorative strategies to

shed light on the implications of too distant sources of knowledge. We furthermore


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highlight the notion of ambidextrous innovation and address how a virtual community

holds potential to reinforce a balance between exploitative and explorative R&D

strategies.

In summary, Q1 helps us identify a problem, Q2 proposes a solution and Q3 assesses the

proposed solution in the light of scope of exploration and ambidextrous organisational

capabilities. Thus, in reaching our succeeding conclusions, this paper follows two logics

of reason. In exploring Q1 a practical and diagnostic approach is taken and our

subsequent findings are largely based on the case analysis of Novozymes through

empirical data from a set of interviews. Our case provides a context in which the

phenomenon of VC can be discussed and exemplified. In Q2 and Q3, our concluding

remarks are the result of inference from extant literature and application and

reconstruction of prevailing theory and concepts, and thereby of a more general nature.

Altogether, we hope to shed light on the emerging phenomenon VC with regards to

innovation and external knowledge sourcing.

1.3. Demarcation It is important to note that there is more to the story of building virtual communities for

external knowledge sourcing than what is covered over the course of this thesis. A large

number of factors must be assessed before a decision to build and employ a virtual

research community can be taken. This paper merely tells the story of how a (particular)

firm could potentially to benefit from an initiative like this. We thus take a specific

interest in gaining a contextual understanding of Novozymes, a company that wishes to

establish a virtual community, how a virtual community can facilitate external

knowledge sourcing, and the implications of this. Given the scope of a Master Thesis we

have chosen to omit analysis of how a possible implementation can take place, and

thereby refrain from addressing how knowledge are to be transferred, internalized or

absorbed into the real world setting of the organization from the virtual community.

Another important note on this paper is that it should not be seen as a cost-‐benefit

analysis of the utility of virtual communities in the given context, but rather as a benefit

analysis. While we touch upon both enabling and inhibiting properties of virtual

communities, we choose to delimit our thesis to unravel potential benefits encompassed

by this technology as opposed to its limitations. While this might indicate an asymmetric

emphasis, it seems justified by the scope and objective of the paper. Thus, we delimit our


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focus on two dimensions. We place our research in the upper left quadrant of figure 1.1

below, yet we want to highlight the there are other important dimensions that needs to

be studied in order to gain a more complete comprehension of the phenomenon in

question.

Figure 1.1: Demarcation

Source: Own model

1.4. Motivation We, the authors of this paper, are fascinated by opportunities arising from the fast

developments of information and communication technology (ICT), and in particular,

online tools for communication and collaboration. Furthermore, given our pronounced

specialization in the field of management of innovation, we wanted to conduct a study of

how online tools hold potential to enhance innovative capacity of firms. Two facets of

innovation have driven our research forward. As highlighted in the introduction the

combinatorial perspective of innovation provides an appealing take on understanding

the emergence of ideas, and consequently how and where innovations transpire. Second,

a movement emphasizing the value to be reaped by firms through exploring external

sources of knowledge has emerged in the economic literature under the term open

innovation. Inspired by the principle proposed by Bill Joy, cofounder of Sun

Microsystems, “No matter who you are, most of the smartest people work for someone else”, we

find models for distributed (open) innovation an intriguing aspect of innovation worth

studying further.

1.5 Relevance Given the rapid emergence of new applications of ICT for the purpose of knowledge

sharing and collaboration we find the topic of our study highly relevant. Virtual

communities are today increasingly being used as a tool for crowdsourcing knowledge,

?

?

Implementation

Contextual understanding !

?

Costs Benefits


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yet we find that the underlying elements for why online technologies provide such a

useful tool is understudied. In particular, we find that science-‐based firms who aim to

engage in unguided search of scientific opportunities by means of online technologies

have been largely omitted from the academic discourse. It is proposed here that science-‐

based firms to a larger extent can take advantage of online networks in their R&D

efforts; hence the present paper aims to provide supportive arguments and theory for

better understanding how to take an active role along the emerging trend of virtual

communities in the light of innovation. Moreover, it is believed here that in studying the

phenomenon of virtual communities through the lens of innovation-‐ and network theory

with point of departure in cognitive economics and sociology discourse, we wish to

provide a more nuanced picture of the utility of such technologies in the management of

R&D strategy and innovation. (See section 3 for literature review and research gap

identification).

1.6. Disposition Figure 1.2. Disposition of Thesis

Source: Own illustration


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2. Methodology The aim of the methodology section is to provide the reader with an overview of the

overall research approach, collection and treatment of data, limitations, delimitations

and critique of chosen methods.

2.1. Research Strategy and Design We are conducting an exploratory case study of Novozymes, and highlight the benefits of

a virtual community for external knowledge sourcing in that context. Exploratory

studies focus on finding new insights, to ask questions and to assess a phenomenon in a

new light, and the advantage of exploratory studies is the degree of flexibility and

adaptiveness that the approach provides the researcher with (Saunders et al., 2007).

The exploratory researcher does not approach their project according to any set formula,

hence we set out to generate hypotheses for later investigation rather than illustrating

an actual occurrence of events. As such our case does not tell a story of how, but rather

asks how, and this paper can thereby be seen as an initial effort to shed light on the role

of virtual communities in a particular context that in turn can open up for future

research.

We are inspired by the abductive theory of method, which emphasizes no a priori

hypotheses or presuppositions before initiating the research (Levin-‐Rozalis, 2000; Haig,

2005). Drawing on an exploratory approach, we sat out to uncover and establish a

research hypothesis on the basis of initial project meetings with NZ (February 2011).

Based on this, we identify current and novel concepts that we find to be of assistance in

substantiating our hypothesis (Haig, 2005). In our particular case, we are not only

dealing with a hitherto unknown and completely new initiative at Novozymes, but

theory and literature on the topic is also scarce. We take this circumstance as an

opportunity to further explore the research phenomena; a circumstance that the

abductive logic supports by calling for a cyclical process of checking and rechecking

against observations made, widening and modifying our hypothesis through the process

(Levin-‐Rozalis, 2000). The movement between theorizing and data collection is reflected

in the shift that our research topic has gone through over course of our research. We

started out by looking into design attributes of an online platform to assess how such an

open innovation platform should be constructed. We soon came to realize that there

were other important underlying issues that would need to be addressed prior to


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assessing implementation and architectural attributes of the platform. We turned our

interest to the notion of network structures-‐ as well as types of scientific research (basic

vs. applied scientific research) and its impact on different types of innovation. We thus

experienced a slight shift in our focus area, and began to theorize and collect data to

further assess these theoretical constructs in the light of a virtual community. Here

where we found that current literature and theory inadequately address the particular

intersection of the topics of network structures, innovation and virtual communities.

Figure 2.1. Abductive research method

Source: Own model

As a result of scant elaborative data, literature and theory, to explain this particular

topic of research, our research design was structured to encompass abductive reasoning.

Data are systematically collected and analysed, and re-‐evaluated to allow the initial

theoretical assumptions to evolve in the process of further data collection and analysis

(Strauss & Corbin, 1998). We furthermore re-‐construct prevailing theoretical constructs

and thus our identified hypotheses according to data collected – a reoccurring process of

movement between theorizing and conducting empirical research (Wallace, 1971). This

approach is, furthermore, in line with the paradigm of social constructivism, which

acknowledges that knowledge is generated in the context of social interaction between

the interviewer and the interviewee (Kvale, 1996). In light of a social constructivist

epistemological approach we primarily rely on heuristic reasoning as guidance

throughout the thesis. As opposed to logic reasoning, heuristic reasoning cannot

demonstrate the truth or falsity of a theorem; it can merely augment or diminish our

confidence in a theorem (Polya, 1941). Thus, while logic reasoning is objective, heuristic

reasoning is subjective. In turn, a heuristic proof is provisional rather than absolute, and

it may be completely reasonable yet come to change tomorrow. Consequently, our


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conclusions are the best that can be obtained in the light of an explorative case study

and given the actual state of our knowledge.

2.2. Data Collection To address the identified research question we have utilised both primary and

secondary sources of information, and qualitative and quantitative research methods.

Secondary sources of information play an important role in the forming of this thesis,

and the MIB4 curriculum has inspired us in structuring our research. We take a

multidisciplinary approach to the literature that is assessed and employed, such to cover

cognitive economics, sociology as well as innovation-‐ and network theory, and literature

on Information and Communication Technology and virtual communities. Across these

topics we emphasise and elaborate upon a selected group of theoretical constructs that

we find useful in highlighting essential elements of our research.

2.2.1. Qualitative research methods Qualitative data collected and applied in this thesis are gathered through interviews.

The purpose with qualitative research interviews is to examine the perceptions of the

world from the point of view of the interviewee and thus to comprehend the meaning of

their experiences of a given subject (Kvale, 1996). Opponents of the qualitative method

argue that research interviews may not lead to objective information (Kvale, 1996). But

this can be partly explained by the ontological point of view of these researchers. They

will predominantly be represented within the positivistic paradigm, and therefore claim

that quantitative methods are the only viable and scientifically sound methods (Kvale,

1996). The ontological point of departure for this thesis is that of social constructivism

and we thus understand that interviews will never represent the definitive truth;

information of an objective nature is not possible to achieve, neither is it the aim of our

research method.

Interviews The objective of this section is to shed light upon the type and structure of interviews

conducted. We have primarily relied on in-‐depth semi-‐structured interviews (approx. 1-‐

2 hours per interview), as such interviews are of value for seeking new insights to a given

issue (Saunders et al., 2007). Inspired by McCurdy et al. (2005) we have commenced

4 MIB: ‘Management of Innovation and Business Development’, a M.Sc. degree program at CBS


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interviews by asking grand tour questions based on a range of topics that we sat out to

identify. These allow the informant to describe a ‘regular day at the office’ and gives the

researcher an idea of what the informant perceives to be the most important to stress; a

valuable technique that avoids imposing interviewer bias. Subsequent questions such as

mini-‐tours-‐ and story question methods have built upon preceding questions, to ensure

that we gain the perspective of the informant (Ibid.).

In exploring our research question we identified four overall focus areas that we sat out

to address through out our research and interviews.

1. Open innovation in the context of Novozymes. The initial interviews conducted with key

employees at NZ, took a predominant focus in understanding what is meant with open

innovation at NZ and which relation it has to company core values.

2. Novozymes R&D Organization. The focus here is to gain an understanding of the current

research processes at NZ’ R&D organization, their current model of innovation and

advantages and challenges that the current structure exhibits.

3. Characteristics of enzyme research. The aim is to understand how enzyme research is

carried out, how scientists interact with other scientists and what types of information is

discussed or shared.

4. Online interaction and the potential of a virtual community set-‐up. We address the

potential utility of a virtual community set up in the context of enzyme research where

we discuss opportunities and disadvantages of a virtual community set up.

Interviewee group Table 2.1 provide an interview summary of all interviews conducted as well as an

indication of which focus area that each interviewee has contributed to. Interviews

conducted have been divided up into two categories: 1. Internal, (NZ employees)

including: biotechnology engineers, enzyme researchers and employees from the

innovation office, marketing, sales excellence, customer solutions, corporate branding

and business development. 2. External (enzyme researchers and innovation

management specialists) including: bachelor-‐ master-‐, Ph.D. level engineering students,

and innovation managers and professors. The column named Company indicates which

company the interviewee is from, and in the case of NZ, 2C Novozymes refers to the R&D

Organization, whereas 8X Novozymes refers to the HQ departments at NZ.


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Table 2.1: Interviewee List Internal

Name: Position: Company: Initials Area of In-‐ vestigation

1 2 3 4

1 Thomas Lykke Sørensen

Front End Champion 2C, Novozymes TLS

2 Thomas Rasmussen Business Development Manager

8X, Novozymes TRMU

3 Jesper Duus Nielsen Senior Department Manager 2C, Novozymes JDUN

4 Erik Gromsen Vice President 2C, Novozymes ERG

5 Martin Simon Borcher Senior Department Manager 2C, Novozymes MTBO

6 Carsten Lauridsen Project Director 2C, Novozymes CLAU

7 Sune Sauer Lobedanz Senior Department Manager 2C, Novozymes SULO

8 Mads Bjørnvad Senior Manager 2C, Novozymes MAEB 9 Martin Barfoed Director 2C, Novozymes MAB

10 Henriette Draborg Innovation Platform Manager 2C, Novozymes HDRA

11 Henrik Lund Senior Department Manager 2C, Novozymes HLU

12 Torben Bochlet Senior Director 2C, Novozymes TVB

13 Henrik Bisgård-‐Frantzen Senior Director 2C, Novozymes HBF

14 Thomas Lenhard Senior Department Manager 2C, Novozymes TLHD

15 Sara Landvik Senior Scientist 2C, Novozymes SALK

16 Steen Krogsgaard Senior Department Manager 2C, Novozymes STKH

17 Espen Friis Protein Engineering 2C, Novozymes EPF

18 Jesper Frederiksen Corporate Brand Manager 8X, Novozymes JFRE

19 Mads Madsen Corporate Positioning, Head of Branding

8X, Novozymes MSMS

20 Lars Christian Hansen President, Novozymes Europe 8X, Novozymes LACH

21 Anett Lund-‐Nielsen Colstrup

Head of Sales Excellence 8X, Novozymes ALN

22 Anders Ohmann Global Customer Solutions Director 8X, Novozymes AOH

23 Sebastian Søderberg Business Development and Marketing Director

8X, Novozymes SESQ

24 Kristian Ebbensgaard New Business Development Director

8X, Novozymes KEBB

25 Anders Lund Senior Director Marketing 8X, Novozymes ALUN

26 Peter Stenbak Executive Assistant to CEO 8X, Novozymes PSTB


17

External

Name: Position: Company: Initials Area of In-‐ vestigation

1 2 3 4

27 Jovita Ivanaviciute Global Research & Innovation Vestas JIV

28 Anders Bech Bruntse M.Sc Student DTU Bruntse

29 Jakob Skjold-‐Jørgensen M.Sc. Student KU Skjold

30 Rasmus Marvig Ph.D. Student DTU Marvig 31 Hans Genee M.Sc. Student DTU Genee 32 Johan Fuller CEO HYVE Fuller 33 Peter Kragh Innovation Manager Coloplast Kragh 34 Jacob Bøtter Partner, Author Wemind Bøtter

35 Lars Bo Jeppesen Professor Università Commerciale Luigi Bocconi

Jeppesen

2.2.2. Method of verification

Qualitative data comprise the majority of our data input, and our research approach is

built to overcome the inherent drawbacks of qualitative methods. We recognize that it

can be difficult to determine the number of interviews needed to validate findings, yet

we draw upon the concept of triangulation5 in achieving consistency of inputs from

informants. I.e. we investigate the extent to which information given by one informant

does in fact provide a realistic picture of the situation. Thus multiple sources of data is

utilised to crosscheck the information provided by informants internally at Novozymes

and external to the company. Furthermore, we consult informants after interviews to

check whether he/she agrees with our interpretations and if conclusions made

represent his/her explanations. The objective of applying the method of triangulation is

to increase both the validity, i.e. checking for causality; and reliability, i.e. checking for

observer bias (Saunders et al., 2007). Through applying these methods of verification,

we experienced that interviewees were content with the conclusions and

interpretations that had been made. And in circumstances where a divergence was

found, we were able to elaborate and discuss findings with the interviewee to reach

mutual understanding of our interpretations.

5 Triangulation refers to the use of two or more independent sources of data or data collection within one study in order to ensure that the data is telling you what you think it is telling you, i.e. ensuring validity (Saunders et al., 2007:614)


18

2.2.3. Quantitative research method

The aim of this thesis is to explore how a virtual community can act as brokerage

function and to facilitate external knowledge sourcing. We are analysing the potential of

a hypothetical virtual community, thus qualitative data pertaining to records of an actual

case does not exists. Quantitative data has in this paper has been gathered through a

structured online questionnaire (appendix 2 for online questionnaire). The

questionnaire is formulated on the basis of what we learned during our interviews and

the survey was sent out to approximately 100 people, where we have received 42

responses. As we draw on the social constructivist paradigm, our aim with the online

survey has been to gain more generalizable and comparable insights with regards to

utility of a virtual community in the context of science-‐based firms who seek to explore

external sources of knowledge. The responses given through the online survey are

applied in part II of the analysis where we explore how a virtual community can be

understood as a platform for external knowledge sourcing.

2.3. Critique of methodology

2.3.2. Limitations The key objective in this paper is to shed light on the phenomenon of virtual

communities as a tool for science based firms to expand their exploratory scope. Given

the nature of our case, we are not able to analyse an actual virtual community and the

results and implications of such. In that respect we are to a limited to a prospective

research approach, where we by means of empirical data and theory aim to anticipate

future outcomes. As such, we cannot make use of the benefits of a retrospective study

that looks backwards and examines the actual outcome of a given phenomenon at work.

Moreover, we seek to identify the potential utility of virtual communities in a new

context where this phenomenon has not yet been studied (to our knowledge), and

acknowledge that our subsequent concluding remarks are to a certain extent speculative.

Yet, there are a number of methodological benefits from taking a prospective case study

approach that we wish to highlight. One issue with the post hoc, or retrospective case

study approach is that the awareness of the outcomes of the case gives the researcher a

temptation to “cherry-‐pick” a case that supports a given hypothesis or theoretical claim

and leave out propositions and factual data that does not fit with the author’s plan

(Bitekhtine, 2007). As mentioned, hypothesizing in this paper has taken place over the


19

course of the research process and is thus less contaminated by such bias. Nonetheless,

we as authors of this paper are certainly not free from bias. The leading hypothesis of

this paper is that virtual communities indeed exhibit opportunities for science based

firms to engage in external knowledge sourcing, hence our preconceived ideas regarding

the utility of virtual communities in this context has played a role during the formation

of the paper at hand.

We recognize the limitations of single-‐ case study, where a multiple case study could

provide more generalizable results. Nevertheless, we believe that as the first study of its

kind, it is important to promote depth over scope in order to unravel the underlying

mechanisms in place. Moreover, much of the input used to delineate a set of enabling

properties of VCs for acting as a vehicle for external knowledge sourcing are based on

inference from existing literature and casework on the use of VCs in related contexts.

In taking an exploratory approach our empiric input plays an important role in opening

up for further questions to be considered. In identifying interviewees as well as

respondents in our online survey, we have used a method of pyramiding. I.e. we have

identified appropriate interviewee candidates in a sequential fashion based upon

recommendations from our preliminary round of interviews. We recognize the risk of

interviewee and respondent bias, however we wish to assert that random selection

would not have been viable in this study, given that extensive knowledge of the subject

matter was deemed a prerequisite to receive qualified answers. Furthermore, we

understand that even with the method of random selection, fully unbiased responses are

not completely achievable.

Finally, Novozymes is known as the world leader of enzyme technology and as a

company that has the capital to make investments in projects, as one interviewee

mentioned, “I don’t think any top-‐level manager at NZ has felt that he didn’t have the funds to

engage in a project of need or interest” (TRMU, 2011). There is thus a great deal of prestige

from being associated with NZ, and many students from engineering universities see

great opportunities in working there. Although interview contacts made with master

degree and Ph.D. level students where initiated by ourselves, the informants became

aware of the sponsor behind the project, namely NZ, through the course of the

discussion. Consequently this can have an impact on the data gathered through the

interviews and online questionnaire resulting in biased responses. For the interviews


20

conducted internally at NZ, the initial contacts for the first round of interviews was

made through the project group at NZ, and thereby had an impact on the responses

given. This can all have had a limiting impact on the information given, however, we

have to the extent possible focused on interview verification methods and been aware of

the potential bias while evaluating data for the analysis.

2.3.3. Reliability Reliability refers to whether the data collection methods yield consistent findings. Three

areas are emphasised here: firstly, if measures taken will yield the same results on other

occasions, secondly, if similar observations could be reached by others, and lastly, if

there is transparency in how sense was made from the raw data (Saunders et al., 2007).

Throughout our research we therefore pay attention to the three threats of reliability,

namely time error, subject error and observer influence (Wilson, 2010). We have

gathered data over the course of nine months and conducted interviews in rounds,

ensuring reliability of answers of respondents, and to provide us with an awareness of

the changing contexts related to the case. This inherently increases our chance to reduce

threats of time error and subject error. With regards to observer influence we have

focused on introducing ourselves as Master Degree students from Copenhagen Business

School, and emphasized that the objective of our research has no risk of harming

respondents’ professional standing. Nevertheless, we recognize that we cannot

guarantee that we have successfully overcome the three threats of reliability.

2.3.4. Validity Validity refers to the extent that the methodological approach allows the researcher to

investigate the problem at hand, and is concerned with the level of truth in the data with

regards to the specific problem (Kvale, 1996). Yin (2003) emphasizes the importance of

constructing validity, both in the research design itself, as well as during the data

collection process. Yin points out that this may be especially important to stress in a case

study research, as people often criticize case study researchers for using ‘subjective’

judgments during data collection. In order to increase construct validity, he suggests

three tactics: multiple sources of evidence, chain of evidence, review by key informants

(Yin, 2003).


21

In order to fully grasp the context that we are researching, we have tried to utilize

multiple sources of evidence to help build and substantiate our findings. We draw upon

qualitative both quantitative research methods where we use interviews, and online

survey as well as literature and theory as sources of input. Furthermore, we take an

interdisciplinary approach to provide a more nuanced assessment of the problem at

hand. While we recognize that there is trade-‐off of depth and scope we have favoured a

broad perspective over a narrow with regards to the literature that we draw upon. The

research process in this paper can be characterised as an incremental chain of evidence

build-‐up, where our hypotheses undergo modifications throughout the process.

Together with key contacts at NZ (TLS & TRMU), we identified an overall assumption of

a positive causal relationship between the notion of distant sources of knowledge inputs

and innovative capacity for NZ. We find support for this claim by combining network-‐

and combinatorial innovation theory that allows us to understand the importance of

distant search and the potential value that lies in networks beyond the reach of the

organisation. Hence, through our interviews we have aimed to focus on a variety of

topics as to cover virtual communities, combinatorial nature of innovations and

structural holes. Lastly, in the previous section on qualitative research method, we

addressed how we have arranged for review by key informants throughout the interview

process by allowing respondents comment on their input.

2.3.5. Generalizability

Generalizability is the degree to which findings can be applicable to other research

settings, also referred to as external validity (Saunders et al., 2007). External validity is

more difficult to attain in a single-‐case study (Yin, 2003), however, as suggested by Stake

(2003), a better understanding of a single case could lead to a better theorizing about a

still larger collection of cases. The degree of generalizability of findings is elaborated

upon the in the discussion and future perspectives section (section 7) following the

analysis and concluding remarks.

2.4 Delimitations Delimitations define and narrow the scope of the study in question, and here we present

exclusionary and inclusionary decisions that have been made throughout the thesis.


22

• The case analysis is anchored in the R&D organisation at NZ, meaning that

research is conducted with focus on the structure and processes that reside

within R&D. We will therefore not assess or include how other functions present

at Novozymes that could provide support for external knowledge sourcing or act

to enhance of innovative capacity, such as marketing-‐ and business development

departments etc.

• The social structure of networks theory discusses both community-‐ and

individual dimensions of networks. We are particularly interested in the

underlying notions of the theory and the effect networks, structural holes and

bridging has on innovation. Thus we omit from distinguishing the community-‐ vs.

individual dimension level network structures.

• We take a particular interest in assessing the potential of a science-‐based virtual

community for researchers that is initiated by a B-‐2-‐B firm. The analysis will

therefore not encompass other forms of virtual communities often employed by

B-‐2-‐C companies such as lead-‐user-‐ or challenge-‐based communities.

Further delimitations that are of interest for the research scope will be elaborated upon

in Literature Review and Research Gap (section 3).

2.5. Central Concepts A number of concepts are employed throughout this thesis. Many concepts are adopted

from prevailing theory and literature and have been outlined in the subsequent

literature review and theoretical discussion sections. Nevertheless, we develop and

make use of several terms and concepts that we wish to describe here in more detail.

Technological vs. organisational innovation We acknowledge that is there is a distinction between technological and organisational

innovation. The former relates to how firms commercialise new technological

knowledge and ideas that result in new products or processes, while the latter referrers

to changes to organisational structures and administrative processes (Poole & Van de

Ven, 1989). We draw on both of these definitions as we address both the impact that a

VC as on the organizational design of our case company, as well as capacity for

producing commercial innovations in the light of exploitative-‐ and explorative R&D

strategies.


23

Innovative capacity The concept of innovative capacity provides a way to understand and measure

fundamental aspects of the ability of a firm to research and produce innovation. While

we do not set out to measure innovative capacity, the term is used to denote the

aptitude of a firm (in our case Novozymes) for producing innovation by means of its

R&D efforts. In behavioural science literature we find evidence of use of the term in

addressing how innovative capacity often is obtained through networks. In other words,

networks can increase the innovative capacity of experimental firms by helping them

secure advantages that they would not be able to obtain on their own (Suarez-‐Villa,

1990). This paper echoes this view of networks and innovation, and recognizes the

importance of networks to ensure innovative capacity.

Incremental vs. radical innovation Incremental innovation can be understood as the continuous learning and development

of existing technology, whereas radical innovation can be understood as the exploration

of new technology that departs from existing practices and structures (Orlikowski,

1991). The view taken on incremental and radical innovation in this thesis is not to be

understood as separate categories but rather as placed on either end of a continuum

representing the degree to which new knowledge (novel combinations) is embedded in

an innovation (Ibid.).

External knowledge sourcing We use the notion of external knowledge sourcing in defining our research question. In

the literature we find that external knowledge sourcing is said to be crucial for

innovation processes, and has been defined as the ability of a firm to recognize,

assimilate and transform knowledge available from dispersed external sources such as

customers, suppliers, other firms, universities, online communities, and industrial

designers is (von Hippel, 1988; Chesbrough, 2003). We define this concept as the ability

of a firm to expand and replenish its knowledge base by means of sources of knowledge

residing external to the organization.

Virtual Innovation Broker The virtual innovation broker (VIB) is a concept used to denote the capacity of a virtual

community to act as a mechanism for bridging structural holes. This concept is

introduced in more detail in the forthcoming theoretical discussion and analysis part II.


24

Discipline Throughout this thesis the term discipline is thoroughly utilized. In the context of our

thesis a discipline is used to denote a particular branch of scientific knowledge or field of

study. Subsequently, cross-‐disciplinary work involves two or more disciplines.

Science-‐based firm Throughout this thesis we use the term science-‐based firm to indicate a company that

uses scientific research as its main input for R&D and technological innovation.

Ambidextrous Innovation We use the notion of ambidextrous innovation to highlight the ability of a firm to carry

out both exploitative and explorative innovation strategies concurrently.

3. Literature Review The literature review section is aimed at identifying a research gap in the current

literature in which the present paper aims to make a contribution. We have set out to

investigate the notion of a virtual community as a mechanism for facilitating external

knowledge sourcing for science-‐based firms. In this effort we review literature on the

topics of Information and Communication Technology (ICT) and Virtual Communities

(VCs) to determine to what extent contributions in the field have addressed our

particular topic of research. On the one hand, the literature review outlined here is a

summary in that we revise extant literature within the field to familiarize the reader

with what has been written on the topic, and to identify a gap in which to position the

present paper. On the other hand, it is just as much a synthesis by way of re-‐organizing

previous findings and claims from extant literature, to give way for new interpretations

that can shed light on the phenomenon under scrutiny. We aim to pinpoint that the

phenomenon of VCs -‐ understood as a mechanism for firms to engage in unguided

search for scientific input to R&D in the external research environment -‐ has been

largely understudied, in particularly through the lens of cognitive economics and

innovation and network theory. First, we position our paper in the field of cognitive

economics, and thereafter move on to revise literature regarding the utility of

incorporating VCs to promote organizational learning. We find that extant literature

inadequately has addressed how science-‐based R&D-‐intensive firms with a strong B-‐2-‐B


25

orientation can utilize VCs as a mechanism for unguided search as a means for external

knowledge sourcing.

3.1. Cognitive Economics A cognitive approach to understanding human activities in the economic arena has

become a fundamental area of inquiry. The field of cognitive economics is developing

into a discipline which is bearing a new theory of human behaviour in economics,

strongly rooted into a cognitive approach to human action (Egidi & Rizzello, 2003).

Cognitive economics can be defined as “…the study of reasoning operations and adaptation

processes implemented by economic agents in their interactions” (Walliser, 2001:3). We adopt

the cognitive approach to economics given the notion that the “...choices people make are

determined not only by some consistent overall goal and the properties of the external world, but

also by the knowledge that decision-‐makers do and don’t have of the world, their ability or inability

to evoke that knowledge when it is relevant…” (Simon, 2000:25). Along the lines of cognitive

economics we take a multidisciplinary approach to our study and concede that the

context in which our research takes place is characterized by structural uncertainty6. In

this particular paper, the notion of search for scientific knowledge in human problem

solving is a central topic, and the conception of innovation lies at heart of our research.

March and Levintahl (1993) point out that firms often find themselves in cognitive traps

in which a strong focus on success may induce them to persist excessively in the use of

procedures and actions associated with success in the past. This tends to anchor firms in

exploitative sub-‐optimal routinized strategies to the detriment of research and

innovation (Ibid.). The central area of interest in this paper is to investigate how firms

can avoid, or escape, such cognitive traps. Our focus is mainly to explore the hypothesis

that a virtual community can act as vehicle for exploration and external knowledge

sourcing and subsequently relieve firms of such ‘traps’. We study the underlying

processes of a particular firm’s (NZ’) R&D activities and its current innovation model to

find that it is to a certain degree trapped in sub-‐optimal exploitative strategic routines.

We further draw on literature in sociology, and on the notions of combinatorial

innovation and network theory, in order to establish that the external knowledge

sources hold opportunities for enhancing the innovative capacity of our case company.

What is of particular interest here, are mechanisms for getting access to unexplored

6 Structural uncertainty: Probability of the occurrence of an unanticipated event due to a particular configuration of a system such as an economy, market or organization (businessdictionary.com)


26

pools of knowledge, and we have chosen to pay specific attention to the role of virtual

communities understood as an ‘enabling space’ or ‘bridge’ between a firm and its

external environment.

There are intense academic debates both regarding more ‘open’ innovation activities,

combinatorial innovation, structural holes theory and around the exploitation-‐

exploration dichotomy, however very few scholars have combined these streams of

literature (one exception is found in Danzinger & Dumbach, 2008). We suggest that an

integrated approach can enrich theory and the workability of these concepts, and in

particular shed new light on the phenomenon of virtual communities. We revise

literature and theory on VCs to determine where in the literature our paper fits.

3.2. Brief history of ICT and the Internet The IT era started in 1971 and transformed society mainly by spurring radical

improvements in computation capacity (see Mores law7) (Jovanovic & Roussea, 2005).

IT has given rise to a successive wave of new technologies including the semi-‐conductor,

and most notably the Internet. While the semi-‐conductor can be thought of as

computational extrapolation of IT, the Internet can be viewed as the communicational

arm of IT. Since the late 1990s the notion of ICT8 (information and communication

technology) is often used to denote these two facets of IT, and in this paper we

predominantly take an interest in the communicational externalities of IT; henceforth

we employ the term ICT.

Since the early days of the Internet era, sceptics and traditionalists have ascribed a

number of risks to the phenomenon of the Internet. It has been said to be potentially

detrimental for the traditional sense of in-‐real-‐world (IRL) social relationships (Dreyfus,

2001). Online social relationships have been described to be less profound, valuable and

durable than offline relationships, and that such communication is often less expressive

and authentic than face-‐to-‐face (FtF) communication. Furthermore, online

communication has been feared to water out human social life dispatching us to the

realms of virtual worlds (Ibid). However, most contemporary research shows that the

Internet has not alienated us from the real world. On the contrary, the Internet has been 7 Moore's law describes a long-‐term trend in the history of computing hardware, i.e. the number of transistors that can be placed on an integrated circuit doubles approx. every two years (Moore, 1965) 8 ICTs and the Internet are used to address a broad range of computer technologies including web browsing, email, chat/instant messaging, online communities, blogs etc.


27

shown to stimulate social and civic engagement and has been said to be the major

catalyst for globalization and the continued progress of the human race (Song, 2008). As

a matter of fact, people are found to be remarkably resourceful in waving the Internet

into existing practices of everyday human life, and instead of abandoning prior social

practices people engage in media multiplicity – the act of using several mediums for

building and maintaining social relationships (Wellman & Haythornthwaite, 2002;

Howard et al. 2004). Essentially the Internet has shrunken the world, yet significantly

enlarged social life, by juxtaposing remote actors online and boosting information and

knowledge sharing. Yet, the literature around this field is nascent and dispersed, and

theorizing-‐ and conceptualizing processes are at work continuously. One of the most

solid concepts to have emerged is that of the virtual community9. The Internet revolution

has evoked an unprecedented proliferation of virtual communities across the web

(Fernback, 1999; Hiltz & Wellman, 1997). The notion of VC is employed as a central

concept in this paper referring to an online ‘space’ where reciprocal interaction takes

place between individuals and groups.

3.3. Virtual Communities The concept of the ‘virtual community’, first introduced by Rheingold (1993), has today

become the pigeonhole for describing ‘places’ where social interaction takes place

virtually through some sort of media, as opposed to in real life (Lavián & Guinalíu, 2005).

While the virtual community concept is as old as the concept of the Internet, its

exponential growth began in the late 1990s due to developments in ICTs such as

electronic mail (e-‐mail), chat rooms and instant message systems (Ibid.). The

justification to this expansion is found in the advantages generated by virtual

communities. Computers send and receive data across remotely located servers that, by

means of a shared interface, facilitate a sense of belonging, collective action and

interpersonal intimacy for humans (Andersen, 2005). Online, people can experience the

benefits from communal life, while avoiding most of its burdens. An individual can

participate in a public ‘place’ while physically being in a private place, and share

thoughts without running the risk of immediate narrow-‐minded judgement. And, in case

conversations grow dull or relationships complicated, a virtual community is always

easy to leave.

9 > 3 million hits on google.com / > 50,000 hits on scholar.google.com


28

Many definitions of the concept of virtual community have appeared in the literature,

but traditionally this concept has been defined from a social point of view. In Reigngold’s

definition, virtual communities are the “…social aggregations that emerge from the ‘Net’ when

enough people carry on those public discussions long enough, with sufficient human feeling, to form

webs of personal relationships in cyberspace” (1993:5). Similarly, Ridings et al. (2002) expose

that a VC is a group of people with a common interest that interact regularly in an

organized way over the Internet. Following Besser online communities are more

narrowly defined as “groups of people with a shared interest in a hobby, profession, or a product

who get and share ideas online. The sharing is done at the convenience of the participant and not

at a specific time of the week or month, and the "meetings," as a result, tend to be ongoing”

(2000:159). It can be inferred that one of the main advantages of VCs is that these

communities can overcome the space, time and physical barriers to interaction that exist

in traditional in-‐real-‐life (IRL) communities (Andersen, 2005). As such, virtual

rendezvous in the form of online groups, networks or communities, challenge the

traditional notion of a community understood as something physically embodied and

dependent on geographical proximity of interacting members. Even so, virtual

communities encompass many of the attributes of IRL communities. Muñiz and O’Guinn

(2001) point out that virtual communities encompass three core components:

• Consciousness of kind: Refers to the feeling that binds every individual to other community

members and the community brand.

• Rituals and traditions: Processes carried out by community members who help to reproduce

and transmit the community meaning in and out of the community.

• Sense of moral responsibility: Reflects the feelings that create moral commitment among the

community members.

While the above highlights many of the characteristics of VCs, little is said regarding the

reason for why individuals choose to engage in communities online. Hagel and

Armstrong (1997) point out that virtual communities can help to satisfy three types of

needs:

• Sharing resources: VCs enable individuals to share information on topics they may be

interested in.

• Establishing relationships: In VCs we may find people with similar problems, interests and

experiences.

• Trading: Some VCs also allow us to carry out economical transactions.


29

While the above list is far from exhaustive, the notion of ‘sharing’ is a reoccurring theme

in most definitions, and can be identified as the substance of online interaction. In

determining how VCs can comprise a source of external knowledge, and potentially

enhance an organization’s innovation capacity, sharing of information, knowledge and

ideas become key components. The proliferation of online communities and interactive

places for collaboration hold the potential to extend the scope of, and access to, relevant

knowledge sources available to an organization (Zhang & Ackerman, 2005). Given that

VCs have enabled new dimensions of interaction and interconnection among

individuals, documents and data, and have become places for people to seek and share

expertise (Ibid.), they have proved to be useful tools for firms in pursuit of new

expertise and knowledge. However the extant literature regarding this topic is quite

scattered and we find that the above definitions and typologies are overly broad in their

scope as they include almost any kind of relationship that takes place across the virtual

space. While they are useful in providing a basic understanding of the concept, they fail

to acknowledge the diverse nature of how and why a VC can be useful, particularly

taking a business perspective. For the purpose of this thesis it becomes important to

differentiate between different kinds of online communities and to consider the

objective that a business may have for facilitating a VC.

3.4. A typology of virtual communities for external knowledge sourcing The diversity of virtual communities (VC) for external knowledge sourcing is quite

remarkable and VCs are today found to meet a plethora of needs unthinkable just ten

years ago. The utility of VCs for knowledge sharing and idea generation has been

illustrated in a large number of studies, and by means of identifying a set of VC

attributes we wish to provide a comprehensive overview. In turn, this will help us to

better pinpoint where in the literature we find our research gap. We identify a set of

community architectures that are fundamentally different, yet all sharing the quality of

acting as catalysts for external knowledge sourcing. We introduce a three-‐pronged

typology of VCs, namely: the user-‐driven-‐, the challenge-‐based-‐, and the research-‐driven

VC. We then pinpoint that the type of community that this paper has set out to study

belongs to the third category. Finally, we highlight in which way this study is different

than other studies of its kind.


30

In order to develop a VC typology, inspiration has been drawn from Pisano & Verganti

(2008) and their classification of modes of collaborative innovation. While this article

does not specifically address ‘virtual’ communities, it acts as a good guiding framework

for understanding different kinds of external networks of innovating firms.

Figure 3.1: Modes of external collaboration

Source: Pisano & Verganti (2008)

3.4.1. User-‐driven community

User-‐, power-‐user-‐ or lead-‐user communities have been recognized to support

innovation and product development across a large number of firms. Von Hippel (2005)

defined lead users as users whose needs significantly anticipate the requirements of the

broader market. However lead users are found to be useless to companies unless they

find a way to communicate and form relationships (Moeini et al., 2006). The phenomena

of VCs have made the lead-‐user innovation concept more widely accepted and exploited;

a number of such successful VCs have seen the light of day. As provided by the

terminology, ‘user-‐driven’ suggest that it is the users of the final products that take part

in product development and the innovation process. This type of community has been

found to be particularly useful for B-‐2-‐C oriented firms (Antikainen, 2011). Two

successful VCs of this kind include Coloplast’s Stoma-‐innovation and Lego’s

Mindstorms.com. This kinds of VC resonates the characteristics of the “elite circle”

outlined by Pisano and Verganti (2008).


31

3.4.2. Challenged-‐Based Community

The challenged-‐based community architecture is structured around pre-‐defined

problem statements or challenges that might be facing a particular firm. In the lingo of

Pisano and Verganti (2008) the challenged-‐based community would resemble that of

the Innovation Mall. Examples of such communities range from one-‐time product design

competitions to extensive expert networks solving complex puzzles. E.g. Henkel

advertised an online challenge called the Henkel “Adhesive Packaging Design Contest”10

where solvers from all over the world submitted their proposals, and a winner was

selected and rewarded. Netflix, the world’s largest online movie rental service provider,

hosted a challenge for developing a logarithm to improve its video recommendation

system. Teams of mathematicians, programmers and software engineers were given

three years to solve the challenge with a subsequent reward of US$1 million. The most

renowned challenged-‐based community is that of Innocentive.com: an online

intermediary innovation broker who broadcasts challenges with accompanying rewards

to a vast network of experts (Lankhani, 2008). We have found that both B-‐2-‐C and B-‐2-‐B

oriented firms utilize this kind of VC.

3.4.3. Research-‐based community In our definition, the research-‐based VC is aimed to source knowledge and expertise

from a global network of a broad mix of industry and university scientists, but also other

individuals interested in the topics addressed by the community ‘owners’/moderator.

The overall goal is to expand the innovation capacity of the firm who choses to establish

the platform. In Pisanos & Verganti (2008) this community bears resemblance to the

Innovation Community in that anyone who is interested are welcomed to join and the

‘search’ is unguided, i.e. not steered by means of predefined problems or queries. The by

far most famous example of a research-‐based community would be that of Procter and

Gamble’s (P&G) Connect & Develop (C&D). It was estimated that for every P&G scientist

there were at least 200 other scientists at least as good elsewhere in the world. Hence,

in 2004 the C&D innovation model was created. C&D is an online initiative based on

global R&D network of scientists and other professionals external to the organization,

who by means of having a clearer sense of consumer needs, work towards identifying

promising ideas and products for the world market (Huston & Sakkab, 2006). In 2010

10 http://www.packdesign-‐contest.com/start.php


32

more than a thousand successful products had been launched with the involvement of

external innovators. Over the years, research productivity has been dramatically

improved at P&G through reliance on a global collaboration platform with people

external to the organization (P&G Annual Report, 2010).

3.5. Research Gap Virtual communities (VC) can be viewed as a relative new phenomenon, dating back less

than two decades. The literature around VCs is embryonic with loosely connected

contributions sprouting up across disciplines. Furthermore, along with new technology

advancements in ICT the phenomenon of VCs is under constant development, making it

a moving target thus difficult to study. By using the typology outlined in below, we can

better isolate our literature gap.

Figure 3.2: Virtual Community Typology

We find that existing literature and case studies examining the utility of virtual

communities as catalysts for external knowledge sourcing to be inadequate. Our

literature gap is two-‐fold, practical and theoretical: Firstly, we find that one of our

identified categories of VCs, namely the research-‐based VC as established in the above,

has been largely understudied. Whether it takes the form of academic papers and case

studies, we find that contemporary work addressing both user-‐driven-‐ and challenge-‐

based VCs occur frequently in the literature with a number of illustrative studies, while

science-‐based research focused communities are close is lacking. Moreover, most

studies on research-‐based VCs relate to initiatives taken by B-‐2-‐C oriented firms, in turn

resulting in a strong end-‐consumer focus. We find that virtual solutions utilized by

science-‐based firm with a B-‐2-‐B orientation to be particularly unaddressed. In this light,

through investigating opportunities of a VC for our case company Novozymes (a B-‐2-‐B

oriented science-‐based firm), we add valuable insight to a new dimension of use of VCs

not yet illuminated. Secondly, we have not come across any piece of literature taking a

User-‐driven VC Challenged-‐based VC Research-‐driven VC • Lead-‐user innovation • Innovation of “use” • Virtual customer environment

• Broadcasting • Solutions seekers and solvers

• Pre-‐defined challenges and rewards

• Virtual research environment

• Knowledge sharing • Collaboration • Unguided Search


33

cognitive economics perspective in addressing research-‐based VCs, neither combining

the theoretical lenses of innovation-‐, network-‐ and ambidexterity theory in this effort.

Finally, we believe we are first to postulate that VCs can by means of certain attributes

overcome obstacles of ambidexterity and thereby ease the often difficult balance of

exploitation and exploration.

In other words, we find that the current literature, by using prevailing concepts and

theory, does not sufficiently address how science-‐based B-‐2-‐B-‐oriented firms can

facilitate a VC as part of unguided search for new scientific knowledge and expertise

with the ultimate goal to ambidextrously enhance innovative capacity. Furthermore, we

test the use of prevailing theory and concepts in explaining the emerging phenomenon

of VC and its implication for external-‐ search, knowledge sourcing and collaboration. It is

our intention to elucidate the phenomenon of the VC in the given context.

4. Theoretical Discussion In this paper we take an exploratory multidisciplinary approach, where we draw upon

and combine literature from sociology, cognitive economics, innovation, and ICT. We

integrate a range of theoretical constructs including: innovation theory, network theory,

structural holes, search, social capital, ambidexterity and virtual communities. The

objective of the theoretical discussion is to provide an understanding of the theoretical

notions and the application of these in the analysis. We have structured the theoretical

discussion into three sections: 1) Combinatorial innovation; 2) Networks, knowledge

and structural holes; 3) Virtual communities and knowledge sharing. On the basis of our

theoretical discussions, we wish to highlight key takeaways with the aim to place our

thesis in the context of these theoretical viewpoints, and to build a conceptual

foundation on which the forthcoming analysis will be conducted. Furthermore, we wish

outline how theory will be applied in the subsequent analysis (section 4.4). Given the

interdisciplinary nature our research and the scope of our thesis, we make reservations

as to how exhaustive the below theoretical discussion is, provided that we have

subjectively chosen theory and concepts.

4.1. Combinatorial Innovation The notion of combinatorial innovation provides an underlying understating of how and

where innovations emerge. It is widely recognised that innovation spurs technological


34

advancements consequently leading to economic growth (Fleming and Sorensen, 2004,

McDaniel, 2000, Klevorick et al. 1993, etc.). According to Schumpeter (1934), innovation

can be understood as “new combinations of productive means,” (in Varian, 2003:1), that,

among others, includes the introduction of a new good. We know that innovation

involves a degree of novelty, however, what exactly is implied by novelty in this context?

Since Schumpeter, the science of ‘innovation’ has received the attention of numerous

scholars (e.g. Henderson; Utterback; Teece; Tushman; Forster; Christensen), all of which

helped define innovation (McDaniel, 2000). The novelty of innovations can be viewed

upon as relative to the overall technological frontier, as well as to the previous

experiences associated with the adoption of an innovation. Novelty thereby refers to the

application of a known technology to a new purpose (Abernathy & Clark, 1985; Afuah,

2004; Fleming & Sorensen, 2004). Afuah (2004) further states that an innovation can be

characterised as invention plus development and commercialization, ultimately opening

up for the recombination of existing technological components and processes -‐ a

combinatorial approach towards innovation (Fleming & Sorensen, 2004).

Re-‐combinations of technological components and processes can take various forms and

produce different results. Freeman and Soete elaborated upon the impact innovations

have, as certain innovations “…involve big changes and discontinuities (‘radical’ innovations)

and others involve many small improvements (‘incremental’ innovations),” (1997:21-‐22). The

notion of combinatorial innovation not only refers to large recombinations of

components but also that smaller alternations in fact can have an impact on the

technological advancement that follows, as well as by spanning way for a transition of

what is perceived to be possible and achievable (Ibid.). Clarifying this idea, we draw

upon Fleming & Sorensen’s (2004) discussion of innovation as the novel

reconfigurations made to a given component or process, ultimately opening up for

technology, product or process advancement. In this thesis we acknowledge the

combinatorial view on how innovations emerge.

How can we understand the origin of combinatorial innovations? And furthermore,

under which circumstances do they arise? Many scholars have sought to provide

insights to this by drawing upon the processes that support the emergence of

combinatorial innovations. In the following, we have identified a number of theoretical

constructs that we find useful in highlighting the notion of combinatorial innovation,


35

and how they apply in the context of our research. Here we take point of departure in

the concepts of the linear model and the chain-‐linked model in highlighting the

importance of science in supporting innovative activities within science-‐based firms. We

then bring in the concepts of exploitation and exploration, and that of ambidexterity to

assess the degree to which NZ is in a position to engage in and incorporate a more

explorative approach in its aim to enhance innovative capacity.

4.1.1. The linear-‐ and the chain-‐linked model -‐ The role of science and innovations Within the fields of innovation management and organisational learning, the notion of a

strong link between scientific progress, technological change and overall economic

development has been emphasised (Bush, 1945; Furnas, 1948; Fleming & Sorensen,

2004). Technological change has furthermore been argued to have an impact on the

competitive structure of many industries, where technological advancements have

driven the growth of industries. As a result industry players non-‐responsive of

technological change and the potential it holds are pushed out of the market (Ernst,

2003). Bush (1945) also emphasises that technological advancements, (i.e. new

products, processes, new industries, etc.) would not come about if it were not for a

deeper understanding and an extensive knowledge-‐base of the laws of nature and the

application of such for practical purposes: “We will not get ahead unless we offer new and more attractive and cheaper products…The answer is clear. There must be a stream of new

scientific knowledge to turn the wheels…” (Bush, 1945: chp.3.5). The focus of Bush’s (1945)

statement is on how to ensure economic development at the societal level and he

emphasises the importance of scientific research that is performed without emphasis on

practical or applied ends. This results in general knowledge and an underlying

understanding of nature and its laws, ranging across scientific fields (Bush, 1945;

Balconi et al, 2010). The findings from conducting basic science are said to substantiate,

and feed into, applied scientific research, thereby supporting the search for a complete

solution that results in a practical application (Ibid). The distinction between basic and

applied science is of importance in understanding the contributions of each, as well as

understanding the interlocked relationship between the two. Bush emphasises that

applied science would eventually stagnate if basic scientific research was neglected

(Ibid). In context of our thesis we find the basic-‐ vs. applied science dichotomy is useful

for understanding the importance of facilitating unguided search for scientific

opportunities as part of NZ’ ambition to enhance its innovative capacity.


36

Below, the linear model and the chain-‐linked model are outlined and discussed. We find it

important to distinguish that the unit of analysis of the two models is quite different,

where the former takes a societal level unit of analysis and the latter takes the

organisation. By juxtaposing the two models we enhance our understanding of firm’s

innovation model. In the context of NZ, we wish to understand to which degree its

internal R&D organisation can be characterised according to the chain-‐linked model.

Furthermore, through understanding the underlying thoughts behind the linear model,

we wish to assess the potential to expand NZ’ current innovation model given insights

provided by the linear model.

Figure 4.1. The linear model

Source: Bush, 1949

Bush (1949) and Furnas (1948) are considered the founding fathers behind the linear

model of innovation (Balconi et al., 2010). The linear model (LM) illustrates the process

of innovation moving from research to marketing (Bush, 1949), or from exploratory and

fundamental research to sales (Furnas, 1948) (see figure 4.1). The LM has been applied

as an influential tool in a broad range of circumstances, such as academics lobbying for

research funds or economists providing expert assertions for governmental policy-‐

makers, justifying financial support for science through the application of the model

(Godin, 2005).

Despite the influential role the linear model of innovation has had, it has stirred much

criticism over the past 50 years. Many scholars proclaim that the linear model

disregards the actual reality of an innovation process. The grounds for such critique

relate to numerous studies that show that the process of innovation is “not smooth nor

linear, nor often well behaved”, implying that the LM is an over-‐simplification of a rather

complex process (Kline & Rosenberg, 1986:285). Kline and Rosenberg (1986) called the


37

linear model into question and introduced the chain-‐linked model as an alternative

model for illustrating an innovation process.

Figure 4.2. The chain-‐linked model

(Source: Kline and Rosenberg, 1986)

They state that the main concerns that the linear model presents is the lack of feedback

loops and the impact on the process of innovating. The process of innovation is in many

cases unforeseeable and characterised by a high degree of uncertainty, may that be

technical, functional or market uncertainty. Radical innovation processes are said to

thrive in environments that allow for the influence of multiple sources of information.

Incremental innovation thrives best where iterative processes open up for new learning

and development, thereby emphasizing the importance of such feedback loops in the

either innovation process (Kline and Rosenberg, 1986). As such feedback loops and

external pieces of information are important drivers for the innovation process:

“innovation in this substance frequently occurs in the processes for producing them –

recombination of existing manufacturing steps” (Fleming & Sorensen, 2004:910). Kline and

Rosenberg (1986) indicate that the linear model, where the completion of one-‐step

ultimately leads to the initiation of the next step, has difficulty in supporting drivers of

innovation.

However, it becomes questionable whether the critique of the LM is in fact valid,

especially if we take a historical perspective of the LM to shed light on what the actual

origin and objective of the model was. The LM was originally designed to support

governments in their pursuit to enhance the economic development after the Second

World War (Bush, 1945). It states that basic or fundamental scientific research is the


38

main and unique source of knowledge for technical innovations hence economic growth,

and the underlying idea takes point of departure in the distinction between basic and

applied scientific research. Private, profit-‐driven organisations are said to lack

motivations for engaging in basic science. Bush stated that it was the responsibility of

the government to ensure that basic scientific research would flourish, and that public

funding would be the driver for such (Balconi et al., 2010), hence he introduced the LM.

However, by direct comparison of the two models we learn that the unit of analysis for

each model is notably different. The chain-‐linked model emphases the innovation

process within a firm, i.e. an innovation process that is characterised by an applied

scientific research approach: technological-‐, application-‐ and industrial oriented

research. The linear model, however, does not refer to the daily processes of

incremental learning and development at the firm level. It looks into the role of science

in enhancing the long-‐term developments of the economy, with particular focus on

science-‐based industries (Bush, 1949; Furnas, 1949). Moreover, it takes a long-‐term

perspective as its unit of analysis; the process of innovation cannot be viewed upon as a

“generalised co-‐occurrence of concomitant tasks” (Balconi et al., 2010:8). In the light of this

thesis, we wish to highlight the importance of distinguishing between the two models

given that the chain-‐linked model does not adequately recognize the importance of pure

basic science, providing important insights that highlight the actual scope of R&D

activities at Novozymes I.e. by understanding science as something that can be

consulted iteratively throughout an innovation process, hence guided by the questions

that arise in that very process, the inventor inherently will suffer from ‘inculcation11 of

the mind’. In other words, the idea behind ‘pure’ science in the discovery of new

knowledge is that “…it is not contaminated by any other value than those relating to the

acquisition of knowledge” (Raucek, 1971:306).

The process of innovation is complex, however, a distinction between basic and applied

scientific research provides insights to the value that can be gained from understanding

the innovation process as provided by the linear model and the chain linked model.

There is furthermore an interconnectedness between basic and applied science; the

success of firm-‐level exploitation strategies might well depend upon population-‐level

investments in exploration strategies (Balconi et al., 2010). It first becomes valid to ask 11 To impress (something) upon the mind of another by frequent instruction and repetition or indoctrination (The Online Dictionary, 2011)


39

to which degree can a firm engage in or establish its own explorative strategies as a

supplement to prevailing exploitative strategies already in place within a firm? In the

forthcoming analysis we aim to elaborate upon the above, through assessing the degree

to which NZ can simultaneously engage in both exploitation-‐level strategies and

exploration-‐level strategies. In pursuit to gain insight to this, the following section

addresses the notion of exploitation and exploration.

4.1.2. Exploitation and Exploration Whether the goal is to take advantage of internal knowledge and developments or to

search for inputs from more distant sources, potentially across disciplines, the concepts

of exploitation and exploration provide valuable insight to the ways in which inventors,

organisations, etc. can engage in such search processes (March, 1991; Fleming and

Sorensen, 2004). In the context of this thesis, the concepts will assist in shedding light

upon the nature of the R&D activities at Novozymes (NZ). Through understanding the

structure of the R&D activities we are able to assess the degree to which NZ is engaging

in exploitation-‐ versus exploration-‐oriented activities, and more importantly the affect

this has on the overall innovative capacity of the firm in light of its aim to expand the

overall enzyme market globally.

According to March exploitation covers elements of search such as refinement, choice,

production, efficiency, selection, implementation, and execution (1991:71). Fleming and

Sorensen (2004) refer to this type of activity as local search. Here the emergence of

input to the innovation process comes from the incremental changes that are made to

one component at a time, either through reconfiguration or replacement of a given

component (Ibid.). The term local indicates that developments are based upon previous

research activities and developments that have taken place, thereby exhausting only the

potential possibilities that lie right in front of the inventor. The benefit of local search is

the possibility to take full advantage of prior research. It also provides the inventor with

a higher degree of reliability in the innovation process drawing on past insights to what

and what does not, act as valuable information in the process of future exploitations

(Fleming & Sorensen, 2004). However, the downside of exploitation is known as

cognitive bias, i.e. by focusing only on familiar components and combinations the

inventor refrains from investigating more distant and potentially more valuable sources

of input. The iteration of exploitation processes can result in a decrease of variability of


40

outcomes, hence slowing down the advancement of innovation as local search

combinations are exhausted over time (Ibid.).

To overcome such cognitive bias, the concept of exploration provides valuable insights.

March states that, different from exploitation, exploration covers elements of search that

indicates variation, risk taking, experimentation, flexibility and discovery (1991:71). The

exploration of new possibilities in an innovation process can provide insights beyond

what local search can open up for. Although exploration can lead to less certain and

systematic inputs as compared to exploitation it can still be of great value, as exploration

leads to inputs that are more distant (March, 1991), thus providing insights to

disciplines that hold potential to produce more novel combinations.

4.1.3. The Ambidexterity Hypothesis

As outlined above, two broad types of qualitatively different learning activities between

which firms divide attention and resources -‐ exploration and exploitation -‐ have been

proposed in the literature (Van de Ven 1996, March 1991). Many studies have shown

that exploration and exploitation require substantially different structures, processes,

strategies, capabilities, and cultures to pursue and may have different impacts on firm

adaptation and performance (e.g. Holmqvist, 2004; Van den Bosch et al. 1999; He &

Wong, 2004). In general, exploration is said to be associated with organic structures,

loosely coupled systems, improvisation, autonomy, and emerging technologies.

Exploitation on the other hand has been referred to relate to mechanistic/bureaucratic

structures, tightly coupled systems, path dependence, routinization, control and

bureaucracy, and stable markets and technologies (Ancona et al. 2001; Brown &

Eisenhardt 1998; He & Wong, 2004). To capture the capacity of managing both these

activities Tushman and O’Reilly (1996) introduced the premise of ambidexterity, which

suggest that firms needs to that firms need to achieve a “balance” between the two to

achieve superior performance. The notion of ambidexterity signifies a firm’s ability to

operate complex organisational designs that provide for short-‐tem efficiency and long-‐

term innovation (Ibid.). Essentially, the two activates compete for firms’ scarce

resources, resulting in the need for firms to manage the trade-‐offs between the two (He

& Wong, 2004). As argued by Levinthal and March, “The basic problem confronting an

organization is to engage in sufficient exploitation to ensure its current viability and, at the same

time, to devote enough energy to exploration to ensure its future viability” (1993:105). Tushman


41

and O’Reilly (1996) use the “juggler” metaphor to describe an ambidextrous firm that

has the capabilities to both compete in mature markets (where cost, efficiency, and

incremental innovation are critical) and develop new products and services for

emerging markets (where experimentation, speed, and flexibility are critical); in other

words to exploit and explore simultaneously. The ambidexterity hypothesis can also be

found in between the lines of Eisenhardt and Martin (2000) who propose that dynamic

capabilities require a blend of both the logic of exploration and exploitation.

In this paper we take a particular focus on innovation processes, and Ancona et al.

argued that dynamic capabilities “are rooted in different streams of innovation—in

simultaneously exploiting and exploring” (2001:658). The literature further highlights that

adopting only one of these methods of innovation would produce insufficient results due

to the shortcomings of each. What is characterised as being good and valuable in the

long-‐term may not be good in the short-‐term and vice verse (March, 1991). This is

elaborated on in Tushman, Anderson & O’Reilly (1997) stating that firm’s face

difficulties in extending their existing competences to develop innovations that would

create new markets. In this light we infer that firms may benefit from separating

activities relating to incremental-‐ and radical innovation respectively.

In this thesis, we employ the notion of ambidexterity to highlight a lacking focus on

explorative R&D activities of our case company. Moreover, we seek to assess the

potential of a virtual community to act as a vehicle for explorative unguided scientific

search without interfering with current R&D practices. In other words, we explore to

what extent a virtual community can make way for an ambidextrous innovation model.

To our knowledge, this is the first study that links the construct of ambidexterity to

virtual community and innovative performance.

4.1.4. Combinatorial Innovation: Models and application of theory Many parallels can be drawn between the concepts discussed up until now. The

concepts of exploitation and exploration are deeply rooted in the discussion of basic

versus applied scientific research, and of the linear model versus the chain-‐linked model.

In the context of exploitation, we therefore recognize a link between the chain-‐linked

model and applied scientific research. We furthermore see an opportunity to congregate

the concepts of exploration, the linear model and the value of basic science. The notions

of exploration and distant search, i.e. gaining input from basic science and cross-‐


42

disciplinary interactions (March, 1991; Fleming & Sorensen, 2004), provides insights to

how a firm can benefit from external sources of knowledge. We infer that the optimal

solution is a combination of both exploitation and exploration, referred to as the

dynamic organizational capability of ambidexterity. In the forthcoming analysis, we

wish to apply these notions and concepts to the case of NZ. Here we emphasize three

models that well capture the notion of combinatorial innovation to help analyze NZ’

R&D activities.

1. The Long Tail of R&D

The long tail of R&D provides an indication of the scope and scale of an organization’s

R&D activities (see figure 4.3). Along the y-‐axis we find the total amount of capabilities

that an organization is able to leverage relative to how cross-‐disciplinary the

organization’s activities are. I.e. the further out on the x-‐axis you move the higher the

degree of cross-‐disciplinary capabilities is captured by the organization. The columns

along the x-‐axis indicate this degree of multi-‐disciplinary engagement of the firm:

• Internal R&D: In-‐house R&D capabilities in targeted disciplines

• External Collaborations: include key customer-‐ and university collaborations

• Multi-‐disciplinary networks: Capabilities leveraged across a broad number of

previously untargeted disciplines

• Unusual Suspects: Unanticipated valuable input found across non-‐targeted

disciplines

• Figure 4.3: The Long Tail of R&D

Source: Own Model (Inspiration: The Long Tail, Anderson 2004)


43

However, due to obstacles to ambidexterity, many firms fail to leverage multi-‐

disciplinary networks and reach out to unusual suspects, to the detriment of more

explorative driven innovation. The model highlights a negative relationship between

depth and scope of the disciplines that a firm leverages and can be understood as the

trade-‐off in balancing exploitation and exploration as pointed out in ambidexterity

literature. By the same token, ambidextrous firms are able to manage capabilities

available across the long tail hence a firm is to be understood as encompassing a range

of the activities on the x-‐axis, as opposed to a simply point on the curve. In the

subsequent analysis, we apply the Long Tail of R&D to map the scope of Novozymes

exploitative vs. explorative activities. The goal is to define NZ’ innovation model and

assess how diverse NZ is given the disciplines leveraged.

2. The external sourcing continuum

An adapted version of the external sourcing continuum introduced by Nambisan &

Sawhney (2007) is outlined below (figure 4.4). The model suggests that firms can “shop”

for innovations ranging from raw ideas to market-‐ready products. The continuum

highlights that there are both benefits as well as trade-‐offs at either end of the

continuum: sourcing for raw ideas takes an explorative focus and provides a company

with a higher degree of reach, i.e. the number of options available, however, it also

implies a higher degree of risk and uncertainty. Sourcing for market-‐ready products

takes an exploitative focus on the refinement of product solutions with a high speed to

market.

Figure 4.4: The External Sourcing Continuum

Source: Adapted model, Nambisan & Sawhney, 2007


44

We propose that focus on applied science, incremental innovation and local search leads

to “shopping” for market-‐ready products at the innovation bazaar, whereas basic

science, radical innovation and distant search result in more raw ideas.

In the forthcoming analysis, we would like to shed light upon this trade-‐off and this

model helps to concretize the dynamic interplay between focus and scope that any

innovation model struggles to balance. We will use this model as part of multi-‐pronged

framework to illustrate the extent of external knowledge sourcing of our case-‐company

and the opportunities that lie in utilizing a virtual community as tool to align

exploitation and exploration.

3. The Chain-‐Linked vs. Linear Gamut

The linear model provides insights to how basic scientific research can be of value for a

science-‐based firm in fuelling applied research activities. We infer that there lies value in

taking basic-‐scientific/linear model approach as complement to applied

scientific/chain-‐linked model reasoning (figure 4.5). In the analysis, we draw upon the

findings of the linear model of innovation and the chain-‐linked model of innovation, and

assess how these provide insights for understanding the advantages and shortcomings

NZ’ current innovation model. More specifically, we investigate the extent to which the

market-‐orientation of the chain linked model inhibits NZ’ to develop novel combinations,

and whether following the reasoning behind the linear model can open up for new front-‐

loading of opportunities to the current R&D organization at NZ.

Figure 4.5: The chain-‐linked vs. linear model gamut

Source: Own Model


45

4.2 Networks, Knowledge and Structural Holes In this section we bring in the notion of networks and structural holes to the theoretical

discussion. In the above section, a number of theoretical constructs have been addressed

as to shed light on the important interplay between basic and applied science, the

process of innovation, and the tradeoff in scope between exploitative and explorative

R&D activities. The network perspective provides important insights that help us to

understand and substantiate the rationale for why Novozymes should engage in external

knowledge sourcing. A thorough understanding of how the social structures of networks

are organized, we are furthermore able to emphasize the value that can be gained from

bridging network structures, which thus opens up for the potential to grasp novel inputs

for combinatorial innovations. The concept of brokerage becomes increasingly

important in this context, as we propose that the virtual community can facilitate the

brokerage of different network structures, a notion that will be elaborated upon in the

sequential section.

In Lahkani and Panetta (2007) principles of distributed innovation is explored,

suggesting that R&D labs can benefit from seizing opportunities residing across

networks external to the organization. The idea is based on Benbya & Belbaly in

postulating that “…knowledge is unevenly distributed in society, and that centralized models for

economic planning and coordination are prone to failure due to an inability to aggregate this

distributed knowledge” (2007:7). We expand Benbya and Belbaly’s notion to suggest that

due to the prerequisite of economic planning of R&D activities in profit oriented science-‐

based firms, such firms generally fail to embrace the full range of distributed knowledge

available to them. In the high-‐tech industry the notion of Joe’s law is prevalent:

“No matter who you are, most of the smartest people work for someone else” (Lahkani & Panetta,

2007:97). Thus, provided that potentially valuable knowledge resides across individuals

and networks outside the boundaries of any organization, taking a network perspective

becomes a critical element in understanding how to best get access to such pools of

knowledge. Essentially, the network dimension of this paper constitute the intersection

between the theoretical constructs previously outlined in the theory section and the

notion of a virtual community in acting as knowledge broker and catalyst for external

knowledge sourcing.


46

In this section we will focus on the concept of networks, structural holes and brokerage

of structural holes (Burt, 1992). To set the foundation in which the remaining discussion

takes point of departure, we begin with a short discussion on the notion of networks,

where the concepts of open and closed network structures is emphasized. Sequentially

we introduce the notion of structural holes that leads to a discussion of the

opportunities and implications to be found, and which affect this can have on innovation.

The aim is to highlight the obstacles and opportunities that arise from structural holes.

4.2.1. The Social Structure of Networks

The notion of social networks has attracted much attention over the past decades from

both the fields of social and behavioral science (Wasserman and Faust, 1994). Building

upon the sociological ideas of Simmel (1955) and Merton (1968), scholars have explored

the concepts of networks, looking into the structure of ties between individuals,

organisations and communities (Granovetter, 1973); the centrality of betweenness

(Freeman, 1977); the power of having exclusive exchange partners (Cook and Emerson,

1978); and the structural autonomy that is created by network complexity (Burt, 1980).

The social network analysis approach also has deep ties within network theory, as it

assumes the importance of relationships between agents. It refers to a set of actors (also

called 'nodes') who are tied to one another through social relations, and therefore takes

point of departure in the relationships that arise among entities, and on the patterns and

interactions of such relationships (Wellman & Berkomitz, 1988). Scholars have

recognized the benefits of applying a social network perspective in leveraging new

insights to standard social and behavioral questions within the fields of political,

economic, or social structural environment (Wasserman & Faust, 1994).

4.2.1.1 Closed versus Open Networks Burt (1997) categorises a number of network benefits according to three main

elements: firstly, a network’s ability to provide an individual with access to information

beyond what he/she could possess alone; secondly, it provides such information early,

which can be advantageous in being the first to act upon it; finally, the network allows

for referral benefits, meaning that the information received through a network is often

considered more reliable as it comes from a credited source (Ibid.). However, it becomes

questionable under which circumstances such ‘information benefits’ are viable. As we

shall see, depending upon the characteristics of the network, and the extent to which it


47

is closed or open, ultimately has an impact on the information benefits to be reaped

from the network (Burt, 1997).

In the social network literature disputes have arisen over which network structure,

closed or open, appropriates the most benefits to the network (Ahuja, 2000). Closed

networks are characterized by strong mutual ties across entities, creating a homogenous

community where everyone knows everyone; the greater the network closure the more

interconnected the network. Coleman (1990) argues that networks with higher closure

generate high trust, which in turn facilitates cooperation. From Coleman’s (1988)

perspective, the optimal social structure of a network is thus one generated from

building dense, well-‐connected networks. Contrary to this, Burt’s (1992) perspective is

that constructing networks of disconnected nodes is the most optimal strategy.

Following this, Burt (1992, 2001) states that there are negative affects of closure: the

high degree of interconnectedness between the members in a closed network results in

the creation of norms in such network structures that make groups less heterogeneous,

thus constraining social behaviors. Burt (1997) goes so far as to say that the structure of

homogeneous closed networks are associated with a redundancy of information benefits,

i.e. no new information is infused into the network. This is echoed by Putman (2000)

who postulates that closed networks are great in helping its members get by, but not

ahead. Due to the homogeneity of the contacts in a closed network, knowledge revolves

within the network without gaining new insights and input to further challenge the

structure (Burt, 1992). Thus non-‐redundant contacts, i.e. unknown contacts and

knowledge can provide information benefits of value to the network itself (Granovetter,

1973; Burt, 1992). A valid remark here is that if a firm’s R&D activities have a strong

internal orientation, the organisation (network) may suffer from what Burt refers to as

redundant information benefits. In the context of this paper, the effect that network

structures (open vs. closed) may have on knowledge sourcing thus becomes important

to consider.

What is particularly interesting in the context of our thesis is the affect that the

characteristics of a network (open vs. closed) have on innovation of NZ’ R&D

organization, and the potential there lies in external sources and networks. Network

structures are said to have an impact on innovation, and it has been is found that small

homogenous communities more quickly introduce incremental improvements in


48

technology (Lynn et al., 1994). Burt (2005) takes this point further in stating that closed

networks might actually work to inhibit innovation (Burt, 2005), while networks with

heterogeneous substructures will produce more radical innovations. NZ seeks to

enhance its innovative capacity through external knowledge sourcing, and therefore the

types of network structures that a virtual community aims to encompass is of

importance. Scholars suggest that open networks hold potential to produce more radical

innovations, and thus it becomes a motivating factor for the remaining discussion to

grasp how heterogeneity of networks and the bridging of networks can be a driver for

innovation.

4.2.2. Structural Holes

A generic research finding in sociology and social psychology is that information

circulates more within groups of people than in between groups of people (Lin et al.,

2001). In other words, in any kind of grouping or cluster of people, such as divisions,

industries and disciplines of research etc., information flows are more vigorous within

than across. This does not necessarily imply that people are not aware of what takes

place in other groups or networks, rather that they focus on the activities taking place in

their particular group, and simply attend less to the activities of people in other groups.

Information flows within groups are results of the cognitive constructs of the individuals

in that group, thereby curbed to fit the cognizance of that group. By the same token, new,

yet ‘unchallenged’ information will circulate more across groups that within, giving rise

to opportunities to emerge in between groups (Ibid.). This idea has been explored more

in depth through the conceptualization of structural holes and the opportunities that lie

in bridging structural holes.

Supporting arguments of the theory of structural holes draws upon network-‐related

theories emerging in the 1970’s. The term structural hole can be characterised as the

social gap between two groups (Parjanen et al., 2011); the weak connections between

clusters of densely connected individuals (Granovetter, 1973, 2005); and as the gaps

between non-‐redundant contacts (Burt, 1997). This element of disconnectedness, in

other words holes in the structure of the networks, may result in ignorance towards the

benefits that could be gained as assets and behaviours get locked in suboptimal

exchanges (Burt, 1980). Thus, potential benefits lie in identifying structural holes across

networks and in taking action in order to attempt to bridge them. In the forthcoming


49

analysis, the research environment of our case company Novozymes (NZ) is analysed,

and we draw upon the concept of structural holes to highlight the rational for why NZ

stand to benefit from engaging in more cross-‐disciplinarily collaborations. In the

following we will review whether structural holes hold opportunities vis-‐à-‐vis

disadvantages, and which role ‘bridging’ and ‘closure’ plays in this respect.

4.2.3. Structural holes and opportunities in segmented networks

Following March’s (1991) idea of exploitation versus exploration, Fleming and

Sorensen’s (2004) notion of local versus distant search, and the notion of social

structures of networks, we come to understand that opportunities lie in distant and

more heterogeneous social structures of networks and that benefits can be reaped

through brokerage (Granovetter, 1974, Burt, 2001, Parjanen et al. 2011). However,

benefits of brokerage are not without limitations and we infer that it becomes vital to

ask: when are structural holes too distant for brokerage to provide fruitful results? In

other words, is there an optimal cognitive distance between structural holes? Following

Nooteboom we learn that “…outside sources of knowledge "require a "cognitive distance" which

is sufficiently small to allow for understanding but sufficiently large to yield non-‐redundant novel

knowledge" (2000: 72). Scholars argue that network structures should optimally hold a

mixture of brokerage and closure (Narayan, 1999). Brokerage of structural holes implies

the existence of brokerage function bridging relationships across heterogeneous actors.

On the other hand, network closure of structural holes results in creating trust and

stronger ties in between previously disconnected agents. There are strengths and

limitations of both closure and brokerage, but “…while brokerage ... is the source of added

value, closure can be critical to realizing [that] value' (Burt 2001:52).

Individuals who are accustomed to interacting with individuals across groups possess

an intuitive ability to accept alternative ways of thinking and behaving and are therefore

able to foresee potential opportunities that lie in bridging activities across various

groups. This notion builds upon fundamental ideas within sociology and economics and

as Adam Smith noted: “when the mind is employed about a variety of objects it is some how

expanded and enlarged.” (Smith, 1982:539). There lies great value in opening up for

discussions between different disciplinary areas, exposing them to means of being and

doing that is unfamiliar to them. Empirical studies further support this notion, as Burt

(2004) noted through an in-‐depth study of a French chemical giant Rhône-‐Poulenc,


50

where the CEO stated that his scientists received great value for new ideas and products

from inputs provided to them from individuals of other disciplinary fields.

4.2.4. Brokerage and Innovation The above discussion sheds light upon the benefits that can be reaped from bridging

structural holes, in that new opportunities arise from connecting unknown areas of

interest, disciplines, etc. The impact that this has with regards to innovation is of due

importance in the context of the given thesis; the objective being to highlight the impact

that distant and unforeseen sources of external knowledge can have on the prevailing

innovation model of a science-‐based company such as Novozymes.

Scholars in innovation and organisational learning discourse has emphasised the

linkages and the outcome of collaborative networks as being the vehicle by which

organisations gain access to external information (Ahuja, 2000). The field of sociology

has long studied the relationship between network structures and innovation, however,

focusing more on the adaption and diffusion of innovation rather than the outcome of

network structures on the generation of innovation (Ibid.). Other scholars have paid

more attention in this area (Shan et al., 1994; Podolny & Stuart, 1995; Powell et al.,

1996). Areas that have been studied range from external factors determining whether

an innovation becomes a technological dead-‐end or if it serves as the basis for

subsequent innovations (Podolny & Stuart, 1995). Moreover, collaborative network

relationships are found positively correlated to innovation output (Shan et al., 1994).

The network perspective on innovation emphasises the importance of the connectivity

of heterogeneous groups of actors as well as the importance of exploring and exploiting

weak ties and structural holes (Parjanen et al., 2011). Networks rich in structural holes

open up for more opportunities for new combinations of knowledge and ideas, and we

thus infer that brokers, or the bridging of structural holes, support innovation by

connecting, recombining and transferring sources of information, knowledge or ideas

that would otherwise be disconnected (Burt, 2004.). Innovation primarily happens at

the boundaries between disciplines or specialisations, and it is therefore evident that

working across boundaries or distances is an important driver supporting innovation

(Parjanen et al., 2011). Hence, the notion of distance plays an important role whether we


51

are talking about cognitive, communicative, organisational, social, cultural, functional or

geographical distance.

Figure 4.6: Bridging network structures across disciplines

Source: Own Model

4.2.5. Cognitive Distance

The concept of cognitive distance supports the notion of structural holes in that it

addresses the degree of “difference” across individuals or groups. Cognition is

developed in the interaction of the physical and social environment and it can be

identified based on prior knowledge, which “…confers an ability to recognize the value of new

information, assimilate it, and apply it to commercial ends” (Cohen & Levinthal, 1990:128).

Following Simon (2000:33), “…cognitive capabilities of human agents are bounded by… the

limits imposed by the frames of reference, value systems and modes of symbolic representation

prevailing in the epistemic communities to which they belong”. This highlights the idea that in-‐

group idiosyncrasies may constrain the cognitive capacity of the group. Nooteboom et al.

(2005) state that the term cognitive in this sense denotes a broad range of mental

activity, perception, sense making, categorization, inference, value judgments, emotions,

and feelings, which all build on each other. Furthermore, as different categories of

cognitive meaning are constructed through the experiences that follow individuals, it is

inferred that individuals inherently interpret, understand and evaluate their

surroundings differently (Nooteboom et al., 2005:3).

Oberoi and Saviotti (2010) introduced the notion of cognitive distance to denote the

dissimilarity in knowledge bases between firms. We thus infer that similarity of

knowledge bases would imply cognitive closeness, likely to prevail within homogenous

networks. The notion of cognitive distance can therefore be understood as the space in-‐

between social structures of networks characterized by structural holes. Conclusively,


52

the diversity of ‘distance’ is to be considered a source of innovation (Harmaakorpi et al.,

2006). In the succeeding analysis (section 6.3.1) we elaborate upon the notion of

optimal distance between structural holes where we place NZ in this context.

4.2.6. Social Capital and Innovation The notion of social capital is a relevant topic to address in the light of this thesis. Given

that we take a network perspective to knowledge creation, the ways in which value is

created by means of relationships becomes a central issue. Moreover, the concept of

social capital can help us to better understand how, and under what premises,

information is shared and knowledge is created. We find that the value of social capital

for knowledge creation is not as straightforward as most authors propose; rather the

value is contingent on context and the type of knowledge one intends to produce. We

come to question if novel combinations (radical innovation) derive benefit from high

social capital, or if in fact the lack of high social capital makes way for this type of

innovation to emerge.

Over the two past decades ‘social capital’ is notably the most successful concept

exported from sociology to other social sciences and to the public discourse (Portes,

2000). Social capital has often been used to address how interpersonal relations can

improve community life and solve social problems. It is a relational asset that exists

across people in a given group, community, organization or society, and that by means of

fostering trust, mutual obligation and cooperation becomes the mortar of civic

engagement (Nelson et al., 2003). I.e., when social capital is high, people feel empathy

with one another and sense of belonging, and they take on responsibilities and

motivation for solving problems (Ibid.).

Social capital represents the gains to an individual, a group of people, or a community,

acquired from the establishment of relations with other individuals or groups. This has

been captured eloquently by Portes: “…whereas economic capital is in people's bank accounts

and human capital is inside their heads, social capital inheres in the structure of their relationships”

(1998:7). Social capital is created when a relationship is established, and appreciates

over the course of repeated interaction (Ibid.). Most scholars agree that social capital

value surplus accrue to both the individual and the collective. Bourdeiue & Wacquant,

define social capital as “…the sum of resources, actual or virtual, that accrue to an individual or


53

group by virtue of possessing a durable network of more or less institutionalized relationships of

mutual acquaintance and recognition” (1992:119).

Social capital: a liability or a virtue? Most literature addressing the notion of social capital seem to praise the emergence of

social capital, and point out a strong positive relationship between social capital and

knowledge creation (Canella & McFayden, 2004). However, high degrees of social capital

have also been seen as a constraint for knowledge creation and innovation.

Interpersonal networks can, over time, produce strong norms and mutual identification

among network members, thus limiting openness to new information and diverse views.

Burt (2001) for example, claims that when high social capital is realized by a group,

norms emerge from such network structures making the group less heterogeneous, thus

constraining social behavior -‐ which from a business perspective can be understood as

inhibiting the innovative capacity of the group. This is echoed by Gabbey & Leenders in

proposing: “When networks are too durable they may yield obstacles for novel combinations of

radical innovation” (2001:203). Nooteboom (1999) recognizes that in the light of radical

innovation (exploration of novel combinations) systemic linkages are not required. In

other words, with novel combination, strong social ties (i.e. high social capital) become a

liability rather than a virtue. Following Lynn et al. (1994), small homogenous

communities are said to more quickly introduce incremental improvements in

technology while innovation communities with more heterogeneous substructures will

produce more radical innovations. This suggests that the value of social capital is

contingent on the circumstances in which knowledge is created, and more importantly,

on the objective of the specific collaborative exertion. In other words, the value that

accrues to a network aimed to produce novel combinations (radical innovation) might

become depressed at expense of high social capital. Walker et al. captures these two

facets of social capital: “Social capital is a means of enforcing norms and behaviour of

individuals or corporate actors and thus acts as constraint as well as a resource.” (1997:111).

From the above, we understand that social capital can be both a virtue and a liability for

a given innovation process, and drawing on this we add depth to our understanding of

network structures and its affect on the outcome of radical vs. incremental innovations.


54

4.3. Virtual Communities and Knowledge Sourcing The structure of networks provides an indication of the opportunities that lie in bridging

structural holes and distant sources of knowledge. We have shown that the structure of

networks is essential for the way in which knowledge can be shared. In the following we

highlight structural characteristics of “virtual” networks, and move on to suggest that as

a result of the properties of a virtual community, it holds the potential to broker

structural holes and distant sources of knowledge. Drawing upon findings of

combinatorial innovations, networks and structural holes, we wish to illustrate how a

virtual community can act to enhance the innovative capacity of Novozymes.

The distance between networks, structural holes and sources of knowledge may come in

different forms such as cognitive, communicative, organisational, functional, social or

cultural. Often the distances are so great that a special brokerage function is needed – a

means by which information exchange and translation can take place between structural

holes (Burt, 2004). In the context of this thesis, we propose that such a special brokerage

function can be facilitated through the means of virtual community, and we introduce

the concept of a virtual innovation broker. We thus proceed to discuss the nature of

information exchange and knowledge sourcing in the context of a virtual community set-‐

up.

4.3.1. Knowledge Sharing and Information Exchange in ‘virtual worlds’

To locate expertise and knowledge sources to solve problems is often a social and

collaborative endeavor (Bian et al., 2008). While performing an online search (using e.g.

‘Goolge.com’) sometimes is an efficient way to answer a particular question, today’s

search engines are not capable of answering queries that require deep semantic

understanding of the query or the document in question (Ibid). Hence, asking a person is

often the only way to get a satisfying answer. One good place to start is then to review

ones own professional network in hope of leads that provide a solution, but sometimes

the right source of knowledge lies beyond the reach and grasp of one’s own network and

‘resources’. The proliferation of online communities and interactive places for

collaboration hold the potential to extend the scope and access to relevant knowledge

sources available to an individual or organization. Virtual communities enable new

levels of interactions and interconnections among individuals, documents and data, and

have become places for people to seek and share expertise (Zhang & Ackerman, 2005).


55

In order to understand how a VC can act as vehicle for external knowledge sourcing,

information exchange and knowledge sharing become important elements to consider.

Researchers have recently positioned social capital as a key factor for understanding

knowledge creation (Nahapiet & Ghoshal, 1998). Here, one important question to

consider is: Why does someone choose to share information or knowledge with

somebody else? Two main rationales or logics come to mind, positioned at two extremes

of a spectrum. First, take the barter economy logic: a pragmatic view of exchange where

an information package is shared in between two individuals just as any other good on a

market, but it is not paid for with money but with the exchange of another good (piece of

information). In the case that interaction repeats itself, a social relationship might

emerge allowing for a social logic to guide the forthcoming exchange. Here, principles of

trust, mutual reciprocity and norms of action allow for information and knowledge to be

exchanged based on principles of social life, as opposed to principles of market exchange

(Bullen, 2007). The two logics of information exchange suggest that information and

knowledge can be shared in both the presence and absence of social capital, but the

characteristics of the exchange is inherently different. The previous point made

regarding the liability of high social capital also bears relevance when addressing

information exchange. We infer that in the absence of social capital, information

exchange follows a more mechanistic/market logic whereas high social capital results in

a more spontaneous exchange following a social logic. Yet, we have learned that high

social capital may run the risk of hampering novel combination to emerge from the

exchange due to the formation of norms and constraints in social behaviour as a result

of group dynamics (Burt, 2001). Thus, there seems to be a trade-‐off between high vs.

low social capital, where the optimal level seems to be balanced level, i.e. neither too

high nor too low, as it fosters an exchange of information that supports the emergence of

both incremental and radical innovations.

4.4. Theoretical synthesis and application In the above discussion a broad number of concepts and theoretical constructs are

introduced and revised, each representing particular dimensions of our topic of research.

Across these concepts we have identified subtle analogies that suggest a relationship in

the context of networks and innovation. We find that many of these, given their

dichotomous nature, can be bifurcated onto a continuum (figure 4.7).


56

Exploitation Local Search

Low Cognitive Distance Closed Networks Closure / Bonding High Social Capital

Incremental Innovation

Exploration Distant Search

High Cognitive Distance Open Networks

Brokerage / Bridging Low Social Capital Radical Innovation

Figure 4.7: Conceptual dichotomy continuum

We find support in Binz-‐Scharf for our claim that exploration and exploitation can be

placed on a continuum and that certain network structures are better suited for each of

the two: “exploration and exploitation…move along a continuum…given by the configuration of

ties in the networks employed. The network is sparse in the exploration phase and dense in the

exploitation phase, corresponding to weak ties during exploration and strong ties during

exploitation” (2003:8). We also infer that the above spectrum falls under the umbrella of

ambidexterity theory, where the balance of each dimension comprises an essential

element for a firm to be ambidextrous. It is at the intersection of the concepts outlined in

figure 4.7, combined with the phenomenon of virtual communities, that the concept of

the virtual innovation broker emerges. Thus, one important contribution of this thesis is

to highlight the utility of virtual communities for science-‐based firm for external

knowledge sourcing, in the light of the relationship between the aforementioned

theoretical constructs. In addition, we find that the models we employ in the subsequent

analysis share a similar pattern. Below we introduce three models that guide us in our

analysis.

Drawing on literature, we understand that firms often find themselves in cognitive traps

in which strong profit-‐orientation may induce firms to persist excessively in the use of

procedures and actions associated with success in the past (March & Levinthal, 1993).

This often leads firms into sub-‐optimal exploitative strategies that impede the

emergence of innovation of a radical nature. One objective of the first part of the analysis

is to analyse to which extent our case company, NZ, is trapped in such sub-‐optimal

exploitative strategies. In doing so, we employ the Long Tail of R&D where we analyse

the external scope of NZ’ current innovation model (see point 1, figure 4.8). Moreover,

although we postulate that firms should be explorative in their R&D strategies, we also

find evidence in the literature suggesting that there is a limit to the value of distant

sources (e.g. Nooteboom et al., 2005).


57

Figure 4.8 Elements of External Knowledge Sourcing

1. The Long Tail of R&D

2. Optimal Scope Continuum

3. Ambidexterity trough a virtual innovation broker


58

This leads us to hypothesize that there is an inverted U-‐shaped relationship between

cognitive-‐, disciplinary-‐ and organisational distance and the degree of valuable input for

radical innovation (see point 2, figure 4.8). Moreover, from the ambidexterity literature

we know that activities relating to the extremes of the continuum (figure 4.7) are often

difficult to combine. In other words, firms often lack the organisational capabilities

enabling a simultaneous focus on exploitative and explorative strategies. It is in this light

that we in the second part of the analysis introduce and apply the concept of the virtual

innovation broker and propose that it can act as a bridge between NZ’ R&D organisation

and more distant sources in the external environment (see point 3, figure 4.8). In sum,

the first illustration places our case company NZ in the context of external knowledge;

the second illustration highlights that resource heterogeneity is valuable, but only to a

certain degree; the third shows that it is not only a matter of scope but also of balancing

exploitation and exploration, and that this can potentially be achieved by means of a

virtual innovation broker.

Given that the second and third part of the forthcoming analysis is of a conceptual

nature, with point of departure in theory and literature, additional theoretical

constructs and how they are applied will be introduced there and then as we see fit.

5. Novozymes -‐ Case Company Profile Novozymes (NZ) is a biotechnology-‐based company headquartered in Copenhagen,

Denmark. The company was founded in 2000 as a result of a de-‐merger12 with Novo

Nordisk, a world leading pharmaceutical company. NZ’ core business areas are

industrial enzymes (94%), microorganisms (4%) and biopharmaceuticals (2%) (Annual

Report 2010). NZ’ products are used in a broad range of process industries including

agriculture, bioenergy, food & beverages, household care, leather, pulp & paper, textiles

and wastewater solutions (NZ Corporate Website, 2011). In large tanks inside the

laboratories of NZ, tiny enzymes are produced using microbiological processes and

fermentation technology. Sustainability lies at the heart of NZ’ business agenda, and

since sustainable solutions have become acknowledged to make sound business sense

by other businesses, NZ profits from delivering green solutions ultimately reducing

energy consumption and climate impact of its customers. NZ is well recognized, both by

12 The split was aimed to bring about a stronger focus on the emerging business of industrial enzymes.


59

the general public due to its green profile, as well as by its customers. In 2010 NZ helped

customers reduce CO2 emission by 40 million tons. Furthermore, the company has

received a number of acknowledgements and rewards: Dow Jones named NZ the

sustainability sector leader in the biotech area and Procter & Gamble appointed NZ its

“Supplier of the Year” for the third year in a row out of more than 80,000 suppliers

(Annual Report 2010). NZ heavily relies on R&D and invests 14% of its turnover in R&D,

and out of its 5400 employees across 30 countries 16% work in R&D (Annual Report

2010). Correspondingly, a strong IPR and patenting strategy is exemplified by an

extensive patent portfolio of more than 6500 granted or pending patents (Annual

Report 2010). After the split with Novo Nordisk and becoming a separate company in

2000, Novozymes (NZ) has experienced steady growth rates. By 2010 NZ had a 47%

market share, compared with 43% in 2000. This makes NZ the world’s leading producer

of industrial enzymes, with generated sales of DKK 9,724 million and EBIT of DKK 2,117

million in 2010 (Annual Report 2010). Given the global economic slowdown, these

results are quite remarkable.

5.1. Novozymes R&D organization The R&D organization at NZ is structured around two functional areas: Applied

Discovery Unit (ADUs) and Molecular Biotechnology (MBs). The ADUs are structured in

divisions along each industrial application area such as textiles, food & beverage,

What is an Enzyme?

An enzyme is a protein that works as a catalyst in naturally occurring processes. Catalysis is defined as the acceleration of a chemical reaction by some substance, which itself undergoes no permanent chemical change. This means that once the biological process is complete, the enzymes are neither used up in the reaction nor do they appear as byproducts.

Enzymes are mostly found in microorganisms such as fungi and bacteria. These are then further developed to improve desired characteristics of the enzyme and prepare it for mass production.

There are a plethora of different enzymes, with highly varying characteristics. Some are good at “chopping up” dirt and fats, suitable for detergents, others prolong life of food, while yet others are specialized at “chopping” starch, helping the fermentation process in ethanol production. When used for industrial applications, enzymes can usually speed up production processes at a lower cost than chemicals due to reduced raw material and utility use.

Source: Novozymes Talent Search, 2011


60

bioenergy, etc. (figure 5.1). The MBs on the other hand are expected to carry out, what

NZ characterizes as basic scientific research and act as a support function the ADUs in

the development of enzymes for each given application area.

Figure 5.1 Overview of R&D activities at Novozymes


The MBs set up project groups that work within each application area, and based on

inquiry from the ADUs, the MBs return to the labs to improve or change characteristics

of the enzyme in question. Most work is centered on optimization and customization of

current products. Such activities include improving enzyme performance and stability

(e.g. to make enzymes in detergents work just as well in low temperatures); improve

process compatibility, i.e. how should the enzymes be applied; and reduce enzyme

production costs (SULO; TRMU, 2011).

A large share of product developments at NZ take place within the four walls of the

organization inside closed labs and protected by a strong IPR policy. Nevertheless, the

R&D organization at NZ has been recognized for its strong focus on external

collaborations (e.g. in Knudsen & Nielsen, 2008). NZ takes an active role in trying to be

more open, as stated on the company website: “One important means of staying ahead is

through mutually beneficial collaborations with universities and other partners around the

world.”13. The collaborative scope of NZ’ R&D efforts can be structured around the

following three activities:

13 http://www.novozymes.com/en/careers/students/how-‐we-‐work-‐with-‐universities/Pages/default.aspx


61

• Internal R&D: A number of in-‐house R&D resources are leveraged. In 2009 the

Innovation Office was set up to manage the front-‐end pipeline across the company’s

businesses, and a number of interactive forums have been created. An intra-‐

organizational communication and connection tool has been set up to make way for

bringing together the company’s employees. Furthermore, a number of group

collaborations have been set up including: NZ' Radical Innovation Catalysts (RIC) and

cross-‐functional group collaboration for idea qualification.

• Strategic partnerships and key customer collaborations: NZ relies on development

projects carried out in close collaboration with external strategic partners as a part

of its growth strategy. Allying with partners in the research process is no longer only

an R&D related decision it is just as much a corporate strategic objective (Knudsen &

Nielsen, 2008).

• University Collaboration: Over the past decade a number of University collaborations

have been initiated by NZ in e.g. the United States, China, Brazil and Denmark. On the

company website it is stated that “By working so closely with universities we get fresh ideas

and talent that help us look into tomorrow to prepare industries for what’s coming”4.

5.2. Looming Challenges The long-‐term targets are set to an annual organic sales growth of 10%, an EBIT margin

of 20% and ROC of 22%, and future projections show that Novozymes (NZ) will hold

50% of the market in couple of years (Annual Report, 2010). Given the current market

situation these targets are to be considered ambitious. While NZ demonstrates an

impressive record, the future holds a new set of challenges that must be dealt with. After

studying the financial numbers more carefully we found that NZ has been outgrowing

the market over the past decade -‐ by a rate of 29%14 (appendix 3). In the long run this

implies that unless total market expansion accelerates, NZ has to grow at the expense of

current market assets, making it increasingly difficult to reach growth targets.

Furthermore, industry concentration is relatively low, with the presence of only a few

manufacturers able to cater to the needs of clients (Frost & Sullivan, 2009). In addition,

the industrial enzyme business is characterised by strong barriers of entry due to

expensive technology and the complex nature of enzyme producing technologies (Ibid.).

Competition is thereby moderate across most enzyme application areas; expect the

14 Novozymes growth divided by total market growth


62

pharmaceutical enzyme market that is highly competitive. Competition is known to

grow markets, and in low concentration industries market growth is highly dependent

on the actions of a small set of competitors (Ibid.). Hence, measures taken by NZ to

ensure market growth are deemed vital for NZ in the future. In this light, innovation and

development of new industrial application areas for enzyme technologies becomes very

important strategic objectives for NZ. Technological change has been argued to have a

great impact on the competitive structure of many industries, where technological

advancements drive the growth of industries (Ernst, 2003). For NZ this calls for constant

development of new applications to meet growth targets, and it is deemed vital to move

beyond existing industries and application areas. NZ has been recognized for its strong

innovative capacity, yet, with future challenges comes greater pressure for pioneering

and radical innovation. As a response, NZ is investigating opportunities to increase its

scope of external knowledge sourcing in order to broaden its horizon in search for new

knowledge. In 2011, a new corporate value pillar was introduced: “Connect to create –

because the world is full of ideas” 15. Furthermore, a “we-‐know-‐it-‐all” corporate culture is

being called into question, which indicates a new direction in which the organization is

moving. NZ is progressively looking for ways in which it can ensure to explore external

sources of knowledge potentially valuable to the organization and the future of enzyme

business.

6. Analysis We conduct a three-‐pronged analysis that combines valuable insights to assist us in

exploring the identified problem statement: How can a virtual community facilitate

external knowledge sourcing so as to enhance the innovative capacity of Novozymes’ R&D

organization? We draw upon empirical evidence, as well as concepts, theory and

literature, as outlined in previous sections of the paper, to support our subsequent

claims and findings. For each part of the analysis a brief part-‐conclusion is outlined, to

be followed by our overall concluding remarks at the end of the analysis.

In the first part of the analysis we aim to gain an understanding of Novozymes current

innovation model and identify the extent and scope of its current R&D activities. Here,

we draw upon empirical findings from our in-‐depth interviews. We conclude that

15 http://www.novozymes.com/en/about-‐us/vision-‐and-‐values/touch-‐the-‐world/Pages/Our-‐values.aspx


63

Novozymes’ innovation model is focused on the exploitation of known sources of

knowledge to the detriment of radical innovation. Ultimately we provide arguments for

why external knowledge sourcing hold potential to benefit the organization.

For the second part of the analysis, emphasis is placed on the concept of a virtual

community, where we develop a rationale behind establishing a research-‐based virtual

community for external knowledge sourcing. We highlight some enabling and inhibiting

properties of virtual communities for acting as a mechanism for unguided distant search

for scientific opportunities. Moreover, we develop the concept of a virtual innovation

broker to highlight that a virtual community holds potential to bridge structural holes.

Here we primarily make inference based on prevailing theory and literature, and also

include findings from an online survey. We conclude that a virtual innovation broker

theoretically holds potential to facilitate an explorative arm of NZ’ innovation model.

In the final part of the analysis we address the notion of scope in unguided search for

scientific opportunities. We bring in the notion of upper limits of ambidexterity and

place emphasis on implications of balancing exploitation vs. exploration-‐oriented R&D

activities in the light of the virtual community set-‐up. Here we suggest that the virtual

innovation broker holds potential to overcome a number of obstacles to ambidexterity

found in the literature. Here we predominantly employ prevailing theoretical constructs

highlighted in the theory section. We conclude that a VC can be viewed as an add-‐on to

NZ’ innovation model with the potential to expand innovation activities to become more

explorative, without harming current exploitative capabilities.

6.1. Part I -‐ Novozymes’ innovation model The objective of the first part of the analysis is to answer the first sub-‐question (Q1) of

the problem statement, namely: To what extent is the current innovation model at

Novozymes conducive for effective external knowledge sourcing? We take point of

departure in the R&D organisation at NZ and aim to identify how R&D activities are

structured with regards to research and new product development. A mapping of the

process of innovation at NZ is conducted, where we draw upon the notion of

combinatorial innovation, concepts of basic vs. applied scientific research and as well as

exploitation vs. exploration. We find that the R&D activities at NZ has a strong in-‐house

focus but also covers a number of external collaborations with key customers and


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universities. A mapping of these provides insights to the scope of NZ’ current innovation

activities transcending organizational boundaries of the firm. Drawing upon the notions

of market-‐pull and technology-‐push and its affect on innovation, the objective is to

address the balance of exploitative and explorative activities in the current process of

innovation.

A mapping of NZ innovation model covers three main focus areas assessed throughout

this section. We begin by looking into the transition that NZ’ R&D organization has gone

through over the past 20 years. This is done in order to illustrate how Novozymes has

moved from carrying out more explorative R&D activities to becoming more exploitative

over recent years. Before concluding on the model of innovation we assess how R&D

project groups are organised at Novozymes to shed light on the degree of cross-‐

disciplinary interactions in R&D projects.

6.1.1. R&D in transition at Novozymes

Innovation is an important driver for economic development for corporations,

industries and society in general (Ernst, 2003). Like most firms, NZ is dependent on

innovation for performance. An innovation model illustrates the mechanisms that act to

support the innovation process, whether it is a result of technology push, market pull or

a combination of the two. In our study of NZ we find that its model of innovation is

currently characterised by the mechanisms of market-‐pull, however, this has not always

been the case. Traditionally, NZ’ model for innovation was characterised by a

technology-‐push orientation where the organisation focused on new inputs emerging

from research (SULO, 2011). This is illustrated by the following assertion: “…when we

found an enzyme and understood why and how it worked, we would then ask if there was a market

that could use it.” (SULO, 2011). R&D activities thus revolved around exploration of

enzyme technologies to discover new enzymes, through working with unknown

components to understand how they worked together (Ibid). The role of marketing and

business development was a secondary activity that followed sequentially after findings

were made in R&D, in order to assess the market opportunities and to commercialise

the product.

The innovation process characterised by technology-‐push did not face much change

until NZ’ product portfolio began to encompass a broad number of product categories


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and application areas. Soon the role of market-‐pull became more crucial, and

optimisation of the current product portfolio was prioritized. Marketing and business

development began to take an active role in determining which industries and markets

were of particular interest for NZ to target, and consequently also where the R&D

organisation was to place its focus (SULO, 2011.). According to employees and managers

at NZ, the shift in this direction has taken place over the last five year, and it

characterises the way in which NZ engages in R&D at present (TLS; TRMU; SULO; MTBO;

SALK, 2010). It is Business Development, Marketing and Customer Solutions that dictate

the direction of the enzyme technology that R&D is researching. This has been further

indicated through our interviews with employees at NZ “…it is business development and

marketing that indicate that there is a particular market with a high potential for enzyme

products, and then we [MB’s and ADU’s in R&D] alter a current enzyme product to meet these

needs” (SULO, 2011). Where R&D activities previously revolved around exploring new

enzymes and solutions, the current model is deemed to be of a more exploitative nature.

R&D today takes point of departure in known enzymes and exploits capabilities built up

internally to deliver optimised products. Innovation at NZ can thus be characterised as

incremental in nature, as most innovations emerge by combining known knowledge and

components to alter current products and build new solutions. Hence we find evidence

that NZ’ innovation model used to be more radically oriented in its approach to R&D

using input from basic scientific research to create new solutions. It seems that over

time the growth of NZ’ product portfolio has influenced a shift in focus of R&D activities,

as indicated through an interview “we [NZ] have such a large palette of products to offer, to

alter, and development further such as to meet the needs of our customers” (SULO, 2011). This is

not to say that the current model of innovation is insufficient16, however it brings to

mind some of limitations in being able to meet future growth projections as discussed in

the company profile above (section 5). Through an assessment of NZ innovation model,

we will shed light upon the extent to which current innovative activities are conducive

for optimally supporting the innovative capacity of NZ in the face of looming challenges

in the future of enzyme business.

16 NZ is clearly able to meet profit targets year after year.


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6.1.2. Novozymes’ innovation model

Taking point of departure in Novozymes (NZ) current R&D focus addressed above, we

assess the degree to which NZ’ innovation model can be characterised in the light of the

chain-‐linked model. We model the process of internal product development given the

frame of the chain-‐linked model to better understand its advantages and drawbacks.

Finally we wish to shed light upon the implications that arise as a result of the chain-‐

linked model in a firm’s pursuit to expand its innovative capacity. On NZ corporate

website it is emphasized how the organization’s innovation model supports incremental

and radical innovative processes with the aim to ensure a solid pipeline of products for

current market needs as well as to ensure long-‐term growth (NZ Corporate17, 2011). We

find reason to call this position into question by means of our assessment of the actual

scope of NZ’ R&D activities. We uncover insights that indicate that NZ model of

innovation is overly geared for exploitation and incremental innovation with a strong

reliance on applied science as the main input.

The combinatorial perspective of innovation highlights that a broad range of inputs from

external sources, feedback on current processes, and organizational learning by

iteration, together act as drivers for innovation. The combinatorial approach is

characterised by re-‐combination of given components, technologies and processes that

in turn accelerate the innovative process (Kline and Rosenberg, 1986). The structure of

the chain-‐linked model supports the combinatorial approach to innovation as it opens

up for both feedback loops and moving back and forth in the process if innovation (Ibid.).

The feedback loops in turn make way for multiple sources of information to influence a

given innovation process – something Kline and Rosenberg argue is beneficial and

supportive of radical innovation (1986). Furthermore, the iteration of processes

supports incremental innovation (Ibid.). Another important characteristic of the chain-‐

linked model is that it supports the design of the innovation process. Initiating a

technological innovation process calls for an overview of what is needed or expected

from the process, and the sequential redesigns that are essential in reaching a successful

outcome (Kline and Rosenberg, 1986).

17 http://www.novozymes.com/en/investor/sustainability-‐investment-‐facts/Pages/rd-‐and-‐innovation.aspx


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Figure 6.1: NZ’ innovation along the Chain-‐linked model

Source: Kline & Rosenberg (1996)

At Novozymes, a market-‐pull approach to innovation takes point of departure in the

needs and opportunities in the market. Our interviews with employees in the MB-‐ and

ADU departments indicate that a large majority of projects are characterised as product-‐

oriented, where the aim is to either work towards finding a solution or to understand a

given solution better; ultimately to produce a better product (SULO, MTBO 2011). When

further asked whether the organisation was involved in other types of projects that

were not pre-‐defined by the market, interviewees from both MB and ADU departments

re-‐emphasised that a vast majority of R&D projects revolved around tailoring a solution

for the market (SULO, SALK, MTBO, 2011).

We infer that processes of development are initiated on the basis of what the potential

market holds of opportunities for a given product, much along the lines of the chain-‐

linked model. Based on a given requirements of the project, the MB project groups work

closely with the ADU division in each given industrial application area in carrying out

continuous re-‐adjustments and refinements until predefined requirements are met

(MTBO, 2011). We draw a parallel between the R&D organisational structure and the

chain-‐linked model, and infer that NZ internal innovation model resembles the

underlying notions of the chain-‐linked model. The process of product development

follows along the path of the chain-‐linked model (Figure 6.1). It takes point of departure

in the potential market, thereby maintaining a strong focus on producing and providing

application and industrial oriented solutions. NZ’ core competences lie within

researching and producing enzymes for industrial purposes, and consequently it heavily

relies on a thorough scientific understanding within the field of biotechnology in being


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able to meet the demands of the market. As outlined in the theory section, the chain-‐

linked model assumes science to be a knowledge domain open for consultation

iteratively over a given innovation process. This implies that science is aimed to answer

questions that arise during the innovation process, which in turn uses identified market

potentials as point of departure. However, developing arguments for why Novozymes

should engage in more explorative R&D, the linear model becomes a useful frame of

reference (see theory section, figure 4.1). The linear model takes a long-‐term

perspective on science in enhancing the lasting developments of the economy with

particular focus on science-‐based industries. The key contributions of this model can

provide valuable insights for NZ in its quest for becoming more explorative. In pursuing

an innovation model that resembles the fundamentals of the chain-‐linked model, we

infer that NZ does not adequately recognize the importance of pure basic science. By

developing mechanisms that invite more basic scientific input, NZ can faster incorporate

emerging developments taking place out in the broader scientific community (figure

6.2). In the following section we assess the role of basic vs. applied science at NZ’ R&D

organization in more depth.

Figure 6.2: Linear Model vs. Chain-‐linked model

Source: Own Model

6.1.3. R&D at Novozymes: basic vs. applied scientific research In the theoretical discussion we established that both basic and applied scientific

research are of great value for an innovation process. Basic science revolves around

generating a general understanding of a phenomenon, and applied scientific research

looks into providing solutions to technological and industrial problems or issues

(Balconi et al., 2010). Through our interviews with scientists at NZ we discovered that

the way in which NZ utilizes these concepts is rather different from the above definition.


69

NZ indicates that its two main R&D departments, MB’s and ADU’s, focus on basic

research and applied research respectively. Yet, taking a theoretical viewpoint a

different story emerges. Novozymes, being a profit-‐driven organization, aims to

strategically focus all R&D and product development activities on delivering market-‐

ready products. It is therefore strategically focused on applied research where all

departments in fact take an application-‐oriented approach to support the necessary

activities throughout the entire pipeline; from early discovery to market launch. This is a

strategic approach that is common for science-‐based profit-‐driven firms, who are often

reluctant to allocate large investments in basic research without a clear future market

value (Balconi et al., 2010). By taking a more thorough look into the activities that these

two departments are engaged in, it becomes clear that the classical definition of basic-‐

and applied research does not apply at Novozymes. As indicated by a Senior Department

Manager for MB Bio-‐Diversity, Martin Borchert, “all research is in fact application oriented,

the differentiation between MB’s and ADU’s merely lies in how early stage we are” (MTBO, 2011).

The relationship between MBs and ADUs is of importance in that both departments

work closely to provide the most efficient products for the industry. Sune Lobedanz,

Senior Department Manager for MB at NZ stated that “the aim of the MB department is not

to investigate a fundamental scientific problem in that sense; a biological problem. We act to

support the ADUs and to bring new insights to the product portfolio” (SULO, 2011). Novozymes’

R&D organisation is structured such that it holds the scientific competences necessary

to substantiate and support the business of the company, and holds the competences to

develop product applications accordingly (SULO, 2011). We therefore call into question

whether the MB department can in fact be characterised to works with basic research,

and therefore also whether the firm is in a position to grasp the value that stems from

more basic oriented scientific research.

6.1.4. R&D project groups at Novozymes A mapping of R&D activities with regards to project formation and the competences that

are utilised indicates a high degree of cross-‐disciplinarily interaction between particular

members of a project group. As illustrated in figure 6.3 the MB department is made up of

a set of sub-‐divisions18, and when projects are initiated, a cross-‐disciplinary group from

18 The MB department is comprised of the following sub-‐divisions: bioinformatics, bioprocess technology, cloning, metabolic engineering, protein chemistry, protein optimization, recombinant expression and screening (NZ Corporate Website, 2011).


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MB is formed to work with the particular ADU division19. The level of cross-‐disciplinary

interaction that takes place internally at NZ is therefore confined to the MB department;

ADU researchers only work within their given industrial application area and not across

(SULO, 2011). Despite this organisational structure, the majority of interviewees

indicated that it would be beneficial for the ADUs to be more cross-‐disciplinary in their

approach, working together in groups across industrial applications (STKH, TLHD 2011).

E.g. people engaged in detergents research could potentially benefit from sharing

experiences and knowledge with people in other application areas such as food or

biofuels.

Figure 6.3: Project groups at Novozymes


When project teams encounter difficulties in finding a solution to a given task, project

groups primarily draw on two means by which they can gain input. They exploit the

internal competences through consulting colleagues and previous research on the area.

Or in the case that the project is in collaboration with an external key customer, the

group has the possibility to consult the collaborating partner for additional input or

guidance (SULO, 2010). NZ collaborative partnerships therefore also play a crucial role

in providing insights to the demands in the market as well as providing guidance with

alternative inputs and suggestions for potential solutions. However, an important

implication is that although the MB department takes point of departure in more early

19 The ADU department covers the following industrial applications: Agriculture, bioenergy, biopharma, food & beverages, household care, leather, pulp & paper, textile, wastewater solutions (NZ Corporate Website, 2011).


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stage research, all activities are nonetheless centered on industrial applications (MTBO,

2011). And the same holds true for projects that involve the collaboration with key

customers. Thus, we find support for our argument that the entire process of innovation

is pre-‐defined to meet a given industrial application outcome, thus limiting the degree of

radical innovations that emerge.

Innovation literature tells us that innovation primarily happens at the boundaries

between disciplines or specialisations, and that working across boundaries or distances

is an important driver in supporting innovation (Parjanen et al., 2011). Following the

notions of combinatorial innovation and structural holes, we have learnt that novel

combinations often emerge across disciplines (from bridging structural holes) and that

there is an incentive to spur interdisciplinary research. In this light we reason that NZ

suffers from a degree of cognitive bias by primarily relying on local search and

exploitation of internal competences in finding input to a given project.

Keeping the above in mind, we infer that there is a continuous flow of knowledge

sharing within the organisation, as well as with collaborative partners in the case that

projects involve their expertise. Along the lines of the chain-‐linked model, R&D at

Novozymes supports feedback loops and iterative processes that enable NZ to

effectively make use if its internal competences, while exploring more distant solutions

is limited to pre-‐defined collaborations with external partners. However, before

concluding on Novozymes innovation model another important point must be

emphasised, which refers to the explorative activities characterised by the above-‐

mentioned collaborative partnerships with key customers and universities. In the

following we draw upon the Long Tail of R&D model to assess the external scope of NZ’

current innovation model.

6.1.5. Novozymes and The Long Tail of R&D Based on numerous interviews with employees and managers at NZ, and by drawing

upon the Long Tail of R&D introduced in the theoretical section, we have developed an

adapted model to illustrate the scope and diversity in NZ’ R&D activities (see figure 6.4).

We use the model to highlight possible limitations of NZ’ current innovation model.


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Figure 6.4: Novozymes and The Long-‐Tail of R&D

Source: Adapted model, inspiration Anderson 2004

The Long Tail of R&D provides an overview of how cross-‐disciplinary R&D activities of a

firm are. The further out the x-‐axis you move the more diverse becomes the set of

disciplines that you leverage. NZ is considered to efficiently exhaust a large degree of its

capabilities along defined and specific lines of enzyme business. While work indeed is of

a cross-‐disciplinary nature, it resides within strategically targeted disciplines as to fulfil

NZ’ objective of supplying products that meet the demands of the market. We have

mapped NZ’ internal R&D as the first pillar along the x-‐axis. External collaborative

agreements with key customers and universities come next. Here, work takes place

across a variety of disciplines some of which are new to NZ, hence these activities are

categorised further out along the x-‐axis. Considering the market circumstances and the

growth projections set for NZ, innovation and the development of new industrial

application areas for enzyme technology are two crucial strategic objectives for the firm.

However, although NZ’ external collaborations indicate a higher degree of diversity of

the disciplines accessed, collaborations are nonetheless close to targeted disciplines

relative to NZ business (TLS, TRMU, 2011). For example, external collaborations with

key customers are conducted within current industrial areas such as collaborative

partnerships with P&G20 on optimizing detergents, or with Schulstad21 on optimizing

20 http://www.pg.com/


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enzymes for baking (Ibid.). University collaborations may indicate that NZ gets access to

more basic oriented scientific research. However, given NZ current focus aimed towards

industrial applications, university collaborations too are found to predominately take

place within known industrial application areas (TLS; TRMU, 2011.). It becomes

questionable whether the current innovation model, characterised by high reliance on

internal competences and external collaborations limited to analogous disciplines, can

in fact support NZ in its goal to expand the market through opening up for more and

new industrial applications.

Explorative and distant search relates not only to acquiring knowledge and ideas

outside a company’s four walls, but more importantly it invites knowledge and ideas

from distant, unique and often unanticipated sources or connections. We infer that there

is a lack of diversity in the input NZ receives and incorporates in its innovation process.

In other words, a vast majority of activities lies within the comfort-‐zone of known

application areas. Furthermore, a strong R&D organisation revolving around the

methods of the chain-‐linked model acts to reinforce NZ’ position in this comfort-‐zone. As

an internal driver for innovation, the model is currently sufficient in fulfilling NZ’

objectives as it supports the development of products for the market. However, the

model is deemed inadequate for enhancing innovative capacity beyond current activities.

We suggest that Novozymes finds itself in a cognitive trap of suboptimal routinized

exploitative strategies. Moreover, we claim that there lies an opportunity in moving

further out along the long tail of R&D to seek and appropriate distant and more diverse

sources of knowledge.

6.1.6. The emergence of revolutionising technologies for enzyme research

To further assess why Novozymes is to benefit from explorative and more distant

sources of knowledge and ideas, it is of interest to understand where revolutionary

technological advancements utilized by Novozymes has come from in the past.

Advancements within research can be said to fall into two categories: advancements

within basic science and advancements within applied science. We have found that a

number of revolutionary technologies that have radically impacted the way, in which

research is conducted across a broad range of fields, also have had a significant impact

on the way enzyme research is conducted today. One such example is that of human 21 http://www.schulstad.dk/


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genome sequencing technology, which was initially developed to understand genetic

codes in humans. Following the notion presented by Bush (1945) this type of research

can be classified as basic scientific research for two reasons. Firstly, government funds

where the supporting backbone of the research initiative -‐ an investment that very few

profit-‐motivated companies would be willing to bear due to the uncertainty of outcomes.

And secondly, the aim of human genome project was to gain an understanding of a

particular scientific phenomenon. The result of this research project starting in the

1960’s turned out to revolutionise the scientific field of medicine through gaining a

better understanding of diseases and cures for human beings (SULO, 2011). In the

beginning 21st century the technology became more accessible and a wider range of

scientific fields started to incorporate the method for the sequencing of other biological

organisms.

Since the year 2000 genome sequencing has played a vital role within the field of

enzymes and biotechnology (SULO, 2011). Sequencing is a commonly applied

technological process at NZ, which has dramatically eased the process of finding

upcoming enzyme candidates, and opened up for the ability to sequence

microorganisms, fungi and bacteria. One response from our interviews stated, “…it has

changed the way we work with micro biotechnology the most” (Ibid.). This technological ability

is of great value to both the way in which NZ works and the external enzyme

environment; it is said that we only know a small share of microorganism what can

actually do. However with the sequencing technology researchers have the potential to

grasp the full potential of these organisms (SALK, 2011).

Another important revolutionising technological change that NZ has encountered is that

of the polymerase chain reaction method (PCR). Originally developed to detect the

mutation causing sickle cell anemia in whole genomic DNA (History of PCR, 2011). The

PCR method replaced an unreliable and inconsistent method that had been developed

internally at NZ, ultimately opening up for more efficient and reliable processes for

cloning microorganisms with consistent outcomes (SALK, 2011). The above examples

shed light on the close relationship between findings in basic science and its ultimate

impact on application-‐oriented research. From interviews conducted we have found that

significant advancements within the field of enzymes have come from unanticipated

sources within basic scientific research (SULO; TRMU; SALK, 2011).


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Furthermore, in the theory section we introduced the linear model to highlight that the

emergence of new scientific knowledge, originating from basic scientific research, is a

driver for initiating application-‐oriented research (Balconi et al., 2010). We find that this

notion holds true in the case of NZ as incorporation of basic scientific inputs as a tool in

application oriented scientific research has been shown to comprise an essential

element in enhancing NZ innovative capacity to date. Thus, it seems important that an

innovation model can exploit both internal capabilities as well as tap into the external

scientific environment.

6.1.7. Conclusion: analysis part I

The objective of the first part of the analysis has been to assess the extent to which the

current innovation model at Novozymes is conducive for effective external knowledge

sourcing. The following concluding remarks are based on what we have learned about

the processes and procedures of R&D at NZ. While NZ claims to be engaged in both

incremental and radical innovation processes, our findings indicate that NZ today is in

fact rather limited to an incremental scope of innovation, and less explorative than seen

in the past. Moreover we find that NZ predominantly relies on market-‐pull logic with

regards to new product development. As a result we find that both MBs and ADUs are

engaged in market captive R&D with a strong application orientation. Nevertheless,

some of our findings also support the presence of exploration activities, such as the way

in which project groups are formed with emphasis on cross-‐disciplinary teams, and by

means of the external collaborations that NZ in fact engages in. Yet, the majority of

research and collaboration with external sources reside within targeted disciplines and

known industrial applications areas. With the challenges confronting NZ, the current

model of innovation plays havoc with the development of more radical innovation with

regards to enzyme technology. We thus infer that NZ is trapped in an exploitative model

of innovation geared for incremental innovation. By drawing upon the notions of the

linear model, we propose that Novozymes is to benefit from unguided search of

scientific opportunities, thereby front-‐loading the R&D organisation through expanding

the current innovation model to leverage basic science and become more explorative.

However, it is deemed a complex challenge to engage in more exploration and basic-‐

science oriented research without compromising the present, very efficient yet

exploitative model of innovation.


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6.2 Analysis Part II – Virtual Innovation Broker In Part II of the analysis we explore the second sub-‐question of our research (Q2) to

understand how a virtual community (VC) set-‐up can support the facilitation of external

knowledge sourcing. The aim is to determine the extent to which a VC can extend NZ’

innovation model to take on a more explorative quality. We develop a set of theory-‐

based arguments for how a number of VC properties can help facilitate an enabling

space for exploration. In the first part of the analysis we reached an empirical and

evidence-‐based conclusion with point of departure in the case of NZ; in the second part

of the analysis we mainly deduce our findings from theory and secondary case-‐

observations. First, by combining theoretical constructs from sociology, network theory

with the perspective of combinatorial innovation we provide an underlying rationale for

why it is valuable to tap into knowledge pools and opportunities that lie external to the

organization. Secondly, by combining our understanding of social structures and its

impact on combinatorial innovations in the light of the idiosyncratic environment of VCs,

we arrive at a set of enabling and inhibiting properties of VCs for acting as a vehicle for

external knowledge sourcing. The guiding hypothesis in this paper is that a VC can act as

a brokerage function between a firm and its external environment. Based on this notion

we introduce our exposition of a VC in this context by developing the concept of the

virtual innovation broker. Ultimately, we conclude that VCs hold potential for acting as a

virtual innovation broker.

6.2.1. A great place to start Novozymes (NZ) is renowned for its strong innovative capacity, yet as outlined in the

first section of the analysis we find evidence suggesting that NZ finds itself in a cognitive

trap of sub-‐optimal exploitative R&D strategies. Given its current model of innovation,

NZ becomes increasingly less likely to produce innovations on the radical side of the

innovation continuum22. Two broad conceptualizations of innovation are considered

important in the light of this paper: open innovation and combinatorial innovation.

Through our interviews at NZ we have come across two statements that illustrate these

two notions well. Per Falholt, CSO23 at NZ said that “…Only 1% of enzyme people work at

Novozymes” (HDRA, 2011). Understanding that most smart people work for someone else

is somehow the essence of open innovation. Thus, just as Procter & Gamble (P&G) in 22 The innovation spectrum refers to the continuum that spans from incremental to radical innovation. 23 CSO: Chief Scientific Officer


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developing the Connect & Develop platform established an understanding that for every

scientist employed at P&G there were at least 200 equally competent scientists

elsewhere (Huston & Sakkab, 2006), NZ have reached a similar conclusion. Second,

Anders Ohmann, Director of Global Customer Solutions at NZ illustrated a way to

understand the notion of discontinuous (radical) innovation: "…the next generation of cars

will likely be developed with the help of the car industry or similar and related industries, however,

if the horse carriage industry had been responsible for the development of the next mode of

transportation, the car would never have been invented” (AOH, 2011). A famous Henry Ford

quote similarly goes “If I'd asked my customers what they wanted, they'd have said a faster

horse." In other words, distant and often unanticipated knowledge pools often contribute

to deliver profound innovations. By the same token, Anders Ohmann pointed out that

while NZ needs radically new industrial application areas for its enzyme technology,

these are not likely to emerge from the innovation model that NZ currently pursues.

From the above we can understand that NZ is aware of two important notions: first that

external sources are plenty and important, and secondly, that agents from distant

disciplines and fields will most likely be those who can provide the most radical inputs

for innovations.

Nevertheless, while it is a great start, few rewards will come from simply knowing that

valuable competences reside external to one’s organization and that distant sources

often hold unforeseen inputs. The true value lies in knowing how to attract and explore

such resources. A first step in this direction is to understand the underlying reasons

manifested in the emergence of social structures, and the nature of how ideas come

about. Secondly, a mediating mechanism of some sort must be developed; where in this

paper we have decided to investigate the potential opportunities that lie in using a

virtual community set-‐up as a medium for realizing external knowledge sourcing.

6.2.2. Structural holes and combinatorial innovation In the theory section we established that the flow of information is more vibrant within

than across groups of people, such that people develop similar views of their history, of

behaviors today, and of how to move into the future. Over time information within

groups group often becomes sticky (von Hippel, 1994), which makes structural holes

appear in the social fabric of communication. These holes are missing relations that

inhibit information to flow between groups. The logic behind structural holes is that


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holes emerge as a result of weaker connections between groups. Moreover, such holes

separate non-‐redundant sources of information, i.e. on either side of a structural hole

different flows of information circulate (Burt, 2001). From understanding this, it

becomes clear that disconnected people are more likely than connected people to

operate with different ideas and practices. Furthermore, the more disconnected the

contacts are the more likely it is that a structural hole exists in between. Nevertheless, it

is in the act of bridging structural holes that things turn complicated, but also where the

value of the hole shows itself. In the book Ten Faces of Innovation, authored by IDEO’s

General Manager Tom Kelley (2005), he introduces the notion of cross-‐pollinators, who

are human agents who “…draw associations and connections between seemingly unrelated ideas

or concepts to break new ground”. Cross-‐pollination reverberates the notion of

combinatorial innovation in that it draws upon the principle of combining or

reconfiguring distributed ideas and turning them into innovations. Thus, novel

combinations can be understood to potentially emerge through bridging structural holes.

The bridge relation that spans structural holes is however not to be understood as a

guarantee, it is a probability; given the right contextual circumstances a connection can

bear fruits. I.e. connecting across structural holes can increase the propensity of a

‘productive accident’; or of encountering a new opinion or practice not yet familiar to e.g.

colleagues; or of envisioning a new synthesis of existing opinion or practice (Burt, 2011).

Furthermore, to bridge is not a forthright endeavor and the literature often point out

that a certain brokerage function is key for bridging the holes -‐ a function that will be

elaborated upon in the following section in the context of a virtual communities.

6.2.3. The Virtual Innovation Broker

In the context of structural holes, the notion of brokers or brokerage functions have been

introduced to address that certain agents, connected to multiple and distributed

networks, are able to act as intermediaries and potentially broker information and

aggregate ideas arising across different/distant networks (Kleinberg et al., 2008). In

other words, the bridging of structural holes is often understood to occur by means of

brokerage (Burt, 2000). In the literature brokerage functions have traditionally been

anthropomorphized, i.e. taken the shape of human agents. Given that most people

require nudging before realizing the value of, or even discussing ideas from, outside

their regular work group, a few people do (Burt, 2001). Such individuals are often better

connected across networks and can act as natural brokers of information. To our


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knowledge the idea of a virtual brokerage function has not yet been proposed in extant

literature. In this part of the analysis we would like to explore the notion of what we

refer to as the virtual innovation broker (VIB) -‐ a virtual community that intrinsically

acts as a broker of information and innovation across remote actors or networks. While

the term virtual suggest that any digital communication device or platform for

interacting virtually is captured by this concept, we have delimited the scope of our case

study to investigate the role of a VC in this context. After all, the notion VC has been

identified as the most profound manifestation of communication taking place across the

Internet. In using the term VIB we wish to emphasize the intermediary role that a VC can

play in acting as a bridge between NZ’ current innovation model and the external, more

distant research environment not currently covered.

Should virtual worlds be seen as a completely new context in which familiar social

processes take place, or merely as an odd context in which social processes play out in a

way not generalizable to the real world? Following Burt (2011), we see no obvious

reason for why networks should operate very differently in VC than across a variety of

in-‐real-‐life (IRL) networks, in which their effects have been reported. In Bakshy, Arrer &

Adamic (2009) (on network contagion effects, gesture diffusion, social trends, fashion in

online vs. offline networks) many attributes of social networks are found to be similar in

both virtual-‐ as well as IRL communities. Moreover, Burt (2011) shows in a study of two

virtual communities that the underlying mechanisms for structural holes and network

closure are the same in both online communities and in offline communities. Thus for

the purpose of this paper we assume similarity between how structural holes are

bridged and combinatorial innovations emerge in IRL communities and in virtual

communities, i.e. understood as familiar social processes that take place in a new

context.

In developing the concept of the virtual innovation broker we study the phenomenon of

virtual communities and some of its properties that support more radical oriented

innovative processes. These findings are essential for the case of NZ, where we propose

that a VC holds the potential to facilitate a brokerage function thus opening up for more

radical innovations to emerge. The following subsections highlight different dimensions

and properties of virtual communities that are of particular interest for our research.


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Virtual communities: structural holes vs. social capital It has been found that recent developments in ICT and the Internet have rapidly changed

the effect of space and time on social capital networks (Social Capital Research, 2011). A

plethora of virtual communities has over recent decades emerged, essentially

compressing the space-‐time continuum by offering cheap and fast connectivity across

remote actors. It has be disputed to what extent an online community actually promotes

or facilitates a place for social capital to grow. Following Wellman (1999) and Cummings

et al. (2002), online communities are not considered to be “intimate groups” due to

geographical dispersion of participants, and such dispersal of social networks should

come to decrease social capital (Putman, 2001). Moreover, the structural holes

argument claims that highly clustered networks are bad for innovative performance

while the social capital position argues the opposite. By extension, the structural holes

argument states that un-‐clustered, or more open networks can enhance innovative

capacity. To explain this discrepancy, one must understand that it takes dramatically

different processes and network structures for producing mature (incremental) as

opposed to young (radical) innovation. For continuous mature innovation, a dense

group of agents addressing similar issues are required to create the critical mass for

further innovation along the ‘chosen path’ (Pyka, 2009). However for a young

innovation to emerge redundant ties are less valuable and it is important to have rapid

access to distant information (geographically, technologically and cognitively) (Ibid.).

Conclusively, structural holes are more important and high social capital less important,

for exploration/radical innovation than for exploitation/incremental innovation, and

vice verse. Thus, what a VC may lack in capacity to ensure intimacy across its members

(i.e. high social capital), it holds in scope and distance across its members (structural

holes). In the light of the virtual innovation broker and opportunities to facilitate

unguided search, exploration and radical innovation, the above discussion further

supports the use of a VIB for this purpose.

6.2.4 Enabling and inhibiting properties of virtual communities

It is argued in this paper that VCs hold a number of enabling as well as inhibiting

properties for supporting external knowledge sourcing. In the literature we find

examples of both skeptics and enthusiasts with regards to how virtual communities

influence social life, knowledge sharing and innovation. The utility of a VC is commonly

assessed by juxtaposing occasions in virtual communities to analogous occasions in real-‐


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life (IRL) communities. First of all, in real-‐life communities geographical dispersion is

often seen an obstacle, however in virtual communities it is rather understood as an

opportunity, where diverging ideas and viewpoints of remote actors can convene and

synergize (Leary & Fontahina, 2007). Furthermore, in case that the mutual topic of

interest is narrow, a large scope is often required as local reach would not be enough for

a community to take form. Take for example ‘Savvyauntie.com’ that gathers thousands

of aunties from across to world online to share experiences, and offers tools such as an

‘Auntiepedia’. It has been described as a modern approach to share and celebrate aunt-‐

hood (Savvyauntie.com, 2011). Such a community is quite unlikely to prosper in a real

life setting. Secondly, virtual communities hold potential to overcome some of the

asocial effects of social interaction. E.g. prejudice is less likely to limit formation of

relationships, as interactions are of a more anonymous nature online. Thirdly, in virtual

communities the impact of differing demographic attributes across members (such as

gender, class, ethnicity, age etc.) is less likely to inflict relationships and ultimately also

information and knowledge sharing, as sometimes seen in traditional “in real life”

communities (Leary & Fontahina, 2007). Fourthly, from the literature we know that

physical communities more often than not suffer from cognitive, disciplinary and

organizational separation. I.e. people tend to group with likeminded people, from within

those disciplines and organizations (workplace, school, etc.) to which they belong. Given

the nature of social interaction in virtual communities, such barriers are to a certain

extent evaded. Finally, according to Rheingold (1993), the main advantage of online

communities is that they hold potential to bring social, intellectual, professional, and not

the least political, leverage to ordinary citizens at low cost. As we see, virtual

communities hold a number of positive attributes for overcoming challenges that often

arise in real-‐life communities.

Nevertheless, while much of the literature address the many positive externalities of

virtual communities, not all literature portrays virtual communities (VCs) in such a

positive light. Fernback wittily argues "…the term virtual community is more indicative of an

assemblage of people being 'virtually' a community than being a real community in the nostalgic

sense" (1999:217). A number of barriers have been identified that VCs have a hard time

to overcome. First, in certain fields, such as the sciences, cutting edge knowledge may be

difficult to disseminate to large groups since it may require specialised expertise and


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may be difficult to aggregate or represent (Olson & Olson, 2000; Bos et al, 2007). As

highlighted by Nooteboom, “new distant-‐shrinking technologies [i.e. ICT] are unlikely to

undermine the value of proximity, because the diffusion of codified knowledge amplifies rather

than devalues the significance of local tacit knowledge” (1999:136). Due to the complex

nature of tacit knowledge, direct and close face-‐to-‐face interaction is essential for new

technological development (Ibid.). A second barrier is the unpredictable shifts in

memberships of a VC. Wenger et al. (2002) pointed out that membership is fluid in its

composition, thus hard work is required for the community to develop and grow -‐ to

maintain energy and a high degree of participation. Thirdly, all large-‐scale, multi-‐user

communities and online social networks that rely on users to contribute content or build

services have been found to share one universal property: a tiny minority of users

usually accounts for a disproportionately large amount of the content and participation,

while a large majority lurk in the background. This phenomenon of online participation

inequality was first studied by Hill et al. (1992) and has been confirmed in a number of

more recent studies (e.g. McConnell & Huba, 2006). Findings from such studies have

resulted in the 90-‐9-‐1 rule: 1% of people create content (creators), 9% edit or modify

that content (contributors), and 90% view the content without contributing (lurkers).

Figure 6.5: Online Participation Inequality

We recognize that virtual communities comprise a set of both enabling and inhibiting

properties for creating and implementing a successful virtual community (appendix 5

for an exhaustive list). Nonetheless, as highlighted in the delimitation of our research,

we take a particular interest in the enabling properties for facilitation of external

knowledge sourcing. We wish to highlight that VC are found to have the capacity to

overcome three fundamental barriers that are of particular interest in the light of our

research:


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1. Temporal barriers

2. Spatial barriers

3. Barriers of cognitive-‐, disciplinary-‐ and organizational separation

By overcoming obstacles of time and space, connections and interactions amongst

members can to a larger extent take place at the convenience of the individual member.

While, IRL communities are constrained by the prerequisite that members must

physically meet at a particular time and place (Burt, 2011), a VC can span geographical

distance and bridge distant networks. This supports the function of potential brokerage

of previously inconceivable structural holes, as these connections in the network would

not naturally have emerged. Furthermore, as we are exploring the potential to grasp

more distant sources of knowledge to spur the emergence of radical innovations, the

dimension of cognitive-‐, disciplinary-‐, and organizational separation are of importance.

In the theoretical section we established that network structures characterized by a

higher degree of heterogeneity might in fact open up for more radical innovations (Lynn

et al., 1994; Burt, 2005). This is because more heterogeneous communities are not to

such a large extent confined by mutual ties, established norms or redundancy of

information benefits, otherwise characterized as being supporting factors for the

emergence of incremental innovations (Burt, 1997). In the case of a VC, we see the

opportunity overcoming barriers of cognitive, disciplinary and organizational

separation, potentially stimulating the emergence of more radical innovation. We follow

up on this discussion in part II of the analysis in the light of obstacles of ambidexterity.

6.2.5. Trends in community life online Thus far, we have introduced theoretical arguments for why a virtual innovation broker

can act to facilitate the brokerage of structural holes and thereby open up for new inputs

for combinatorial innovations. However, it is also important to assess whether the

notion of a VC fits into the context of a firm that resides in a science-‐based industry. In

doing so we have identified a number of generic trends regarding the use of VCs as well

as gained insights through an online survey where we asked a group of researchers and

biotech students about their habits and preferences for interacting online. Our data

suggests that online interactions are not just a frivolous social endeavor but that it is

becoming a professional act, as researchers increasingly seek to share knowledge and

collaborative partners online.


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Based on the ever-‐increasing number of members of large VCs we sat out to investigate

if the adoption rate is also increasing on a generic level. This would point out that VC life

on a macro level is becoming a more integrated part of peoples’ lives. By comparing the

time it took for the four largest virtual communities today, we found intriguing evidence

of a dramatic increase in the rate of adoption. Calculating the days it took from when

these communities were founded until they reached 20 million users, we identify an

exponential development in rate of adoption (see figure 6.5). LinkedIn founded in 2003

took nearly 2000 days to reach 20 million users, whereas Google+ launched in 2011 only

took 24 days. While there certainly are many variables in play for this development, it

hard to neglect that user adoption rates most positively have increased over the years.

Figure 6.5: Time to reach 20 million users

Source: www.mashable.com

A second finding from browsing a number of blogs and other social media news

websites is that social media is increasingly becoming a popular instrument among

scientists. Niche communities are sprouting up all over the web (Appendix 4 for

exhaustive list of identified of niche science and related VCs). We can thus infer that the

scientific community24 is becoming more responsive towards interaction across VCs. A

plethora of communities is emerging with devoted interests in particular fields of

research. Many of these are also of a rather cross-‐disciplinary nature where scientists

meet from across broad array of fields.

24 The scientific community consists of the total body of scientists, its relationships and interactions (http://en.wikipedia.org/wiki/Scientific_community)


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In summary, two supporting arguments are put forward in the above: 1) Virtual

community rate of adoption is increasing dramatically on a macro level and 2) the

scientific community is becoming more prone to engage in online community life,

substantiated by the emergence of more niche-‐online communities within the field of

scientific research.

Online survey A historical and well-‐documented notion is that a scientist’s motivation for doing

research to a large extent is intrinsic, i.e. “it cannot be enforced…it must come as product of

enthusiasm that an individual feel towards his work” (Glaser, 1965:1). Findings from our

online survey provide indications that substantiate the above statement by Glaser. Here

we found that a large majority of our online survey respondents showed a high sense of

professional pride in their line of work (i.e. researching). More than 80% indicated that

they enjoy being able to help others, that they took pride in assisting others with

problem solving and idea development. More than 70% indicated that being able to

discuss and elaborate on research findings and contemplations with other researchers

drives them. Responses related to the scientist motivation for engaging in research

further reflect the findings of Glaser. 35% replied that it was their passion for the field

and 27% stated that it was their interest in expanding the pool of knowledge that

motivated them (appendix 2). Our online survey provides indications that scientists

aspire to interact with likeminded people who share their enthusiasm, and that they also

value such activities in an online context. Furthermore, amongst the respondent group

from our online survey we were able to spot similar trends as highlighted in above. Our

results point out that researchers and biotech students increasingly use the Internet as a

source for networking, collaboration and knowledge (Appendix 2). Furthermore, with

regards to the online behavior of the respondents, more than 70% saw value in

contributing on online platforms, and more than 60% indicated that they could see

themselves actively partake in discussions and problem-‐solving activities online.

Findings from our online survey indicate that researchers see value in being able to

collaborate with other like-‐minded people, and furthermore, to do so through a virtual

community. In the light of this thesis these arguments are important as they indicate

that virtual communities are increasingly adopted as a knowledge sharing and

collaboration tool, also used by researchers. We thus infer that this behavior on part of


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the researchers further supports our hypothesis that a virtual community hold potential

to act as vehicle for external knowledge sourcing.

6.2.6. Conclusion: analysis part II In the second part of the analysis the objective has been to explore the phenomenon of

virtual communities in the context of innovation and external knowledge sourcing. By

drawing upon notions of social capital, structural holes and brokerage in combination

with a number of virtual community attributes we point out that VCs hold the potential

to bring together remote actors, that would not otherwise naturally meet. In this light,

we develop the concept of the virtual innovation broker to highlight the enabling

properties of a VC in acting as a mechanism for bridging structural holes across

dispersed networks. In this effort we highlight the social context and point out that VCs

can overcome temporal and spatial barriers as well as barriers of cognitive, disciplinary

and organizational separation, all commonplace in in-‐real-‐life communities. We find

supporting evidence of general trends in online community life further suggesting that

virtual communities are becoming a more integrated part of people’s life. Moreover,

niche communities centred on particular areas of interest is yet another emerging trend.

Here we find that researcher-‐oriented communities are finding the Internet increasingly

useful as tool for carrying out research, to collaborate, share and receive knowledge

input. In an effort to quantify these trends we conducted an online survey, where

respondents to a large extent confirmed our claims. Thus, by combing theory, literature

and illustrative cases we find support for our hypothesis, i.e. that the utility of a virtual

innovation broker in the given context is potentially high. In light of taking an

explorative research approach, we find reason to be optimistic with regards to the

potential of a virtual community in acting as a virtual innovation broker and opening up

for more distant and explorative inputs to the current innovation model at Novozymes.

Nevertheless, we recognize that our arguments are inadequate in order for us to

conclude with certainty that a VC can become an explorative arm of Novozymes

innovation model. To provide a more comprehensive view of VCs and explorative R&D,

in the third and final part of the analysis we address the VIB in the light of the notion of

optimal scope in external knowledge sourcing and obstacles of ambidexterity.


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6.3 Analysis Part III – The Ambidextrous Innovation Model Through the first and second part of the analysis we confirm that the current innovation

model at Novozymes is limited in its explorative scope, and that literature and theory

support our notion of the virtual innovation broker as possible tool to expand the scope

of NZ’ innovation model through facilitation of an enabling space for external knowledge

sourcing.

With support from literature and theory we argue that the propensity to produce more

radical innovation increases with distance or separation of actors. However too much

distance may render information irrelevant and incomprehensible (Parjanen, 2011).

Thus there seems to be a limit to the scope of explorative R&D activities. We raise two

issues to be addressed in the third and final part of the analysis: how can the notion of

optimal scope be understood, and how can the virtual innovation broker (VIB) be

illustrated as tool for ambidextrous innovation? We confine our argumentation in this

section to a conceptual level, i.e. we do not aim to address specific functional-‐ and design

attributes of a potential VC-‐platform, but rather by utilizing prevailing concepts in

network-‐ and innovation theory highlight the notion of scope in unguided distant search

for science-‐based firms, such as NZ. Here we seek to illustrate the notion optimal scope

in the presence of virtual communities and unguided search. In the light of the

exploitation-‐exploration dichotomy, literature on ambidexterity provides evidence of

how balancing exploitative and explorative strategies often are found difficult for firms

to achieve. Given the set of properties identified in the second part of the analysis, here

we assess the degree to which a virtual community can be understood as a tool that can

make way for an ambidextrous innovation model.

6.3.1. Optimal Scope Continuum In the theoretical discussion section we highlighted that diversity of distance, cognitive,

disciplinary and organisational, is seen as a source of innovation (Harmaakorpi et al.,

2006) and often emphasised as a precondition for novel combinations to emerge

(Parjanen, 2011). Similarly, too high proximity is said to induce a lack of openness and

flexibility towards new or unknown sources of knowledge (Boschma, 2005; Parjanen,

2011). By the same token, too much distance may render information irrelevant or

incomprehensible. Nonetheless, while high distance holds the merit of novelty (greater

variety), it also holds a problem of communicability from a lack of common ground of


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experience, skills and norms. It is thus important to understand that cognitive distance

must be sufficiently small to allow understanding, but sufficiently large to generate non-‐

redundant novel knowledge. The implication of this in the context of the virtual

innovation broker implies that there is a given limit to the degree of resource

heterogeneity -‐ a limit to the value of the information sourced. We infer that there is an

inverted U-‐shaped relationship between resource heterogeneity and input for radical

innovation. In the Optimal Scope Continuum (figure 6.6) below, we have show that as

cognitive distance increases it has a positive effect on learning by interaction because it

yields opportunities for novel combinations of knowledge and information. Diverse sets

of known and unknown information (i.e. semi-‐redundant information) are necessary for

the potential of novel combinations to emerge in such settings. However, at a certain

Figure 6.6: The Optimal Scope Continuum

Source: Own model

point the cognitive distance becomes so large, inherently rendering the mutual

understanding needed to utilize such opportunities obsolete, in other words, resulting in

redundancy of information. A similar logic can be applied to the notion of exploitation

and exploration. Innovation processes that are characterized by a lower degree of

cognitive distance, i.e. similar to those of NZ’ innovation model, are prone to be more

geared towards exploitation. On the other hand, innovation processes that are

characterized by more distant sources (high cognitive distance) of information by means

of explorative activities open up for more radical innovations.


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Drawing on our findings from part I of the analysis, we understand that the information

and knowledge that NZ’ has access to, both internally through the R&D organization and

externally through its collaborative partnerships, although cross-‐disciplinary in its

nature, nonetheless lie within already targeted disciplines. We therefore infer that NZ

mainly leverages sources characterized by a relatively low degree of cognitive-‐,

disciplinary-‐ and organizational distance, and we map NZ at the far left end of the

optimal scope continuum (see figure 6.6). The information here is of a non-‐redundant

character, which places NZ in a position to conduct primarily market captive R&D. We

infer that information and knowledge that resides further out along NZ’ long tail of R&D

(see analysis part I, figure 6.4) in the external environment provides information that is

of a semi-‐redundant and redundant character. Such information is of value to an

organization in producing novel input for innovation. In the past where NZ’ model of

innovation was more driven by a technology-‐push and explorative approach, NZ gained

access to more basic scientific oriented input. One example highlighted was the DNA

sequencing technology, which ultimately had an important impact on the processes of

innovation at NZ. The technology was originally developed to sequence human genomes

in 1960’s, and at the time it could be categorized as redundant relative to NZ. When the

technology was adapted to fit other fields of research information, became semi-‐

redundant and later non-‐redundant, so that NZ in 2000 was in a position to assimilate

the technology into its R&D processes. We know from theory and from the analysis part

I of NZ, that basic scientific inputs are of value to application oriented R&D, however,

such information must reside within the optimal cognitive-‐, disciplinary-‐ and

organizational distance, i.e. of a non-‐redundant, or preferably and semi-‐redundant

nature to be of value for a firm such as NZ. It is argued here, that by being more

explorative, a science-‐based firm can gain realize the value from developments in basic

science at a faster rate.

What the precise optimal scope of distance is can be very difficult to assess. However,

the optimal scope can be defined according to when information moves from being

semi-‐redundant to being completely redundant, i.e. when the mutual understanding

needed to assimilate new information is no longer apparent, and therefore not of value

for the given innovation process. Hence, the optimal scope continuum recognises that

both exploitation and exploration are of value for a given innovation process, and that


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once distant and more explorative information becomes redundant in the given context,

it provides an indication of where outer limits of exploration resides, hence also where

the optimal scope is be identified. We thus conclude that although it holds great

potential to draw in more explorative and distant sources of knowledge, there is

essentially a limit to the value of exploration. Bearing this finding in mind, in the

following section we on to address how an organisation can balance the two activities of

exploitation and exploration and the role a VIB can play in this context.

6.3.2. Overcoming obstacles to ambidexterity

Ambidexterity can be understood as the interplay between exploitation

(stability/incremental innovation) and exploration (flexibility/radical innovation).

According to March, exploitation includes such things as refinement, choice, production,

efficiency, selection, implementation, and execution. Exploration on the other hand

includes things captured by terms such as search, variation, risk taking, experimentation,

play, discovery, and discontinuous innovation (1991:71). Levinthal and March state that,

“an organization that engages exclusively in exploration will ordinarily suffer from the fact that it

never gains the returns of its knowledge” (1993:105). In contrast, firms mainly in pursuit of

exploitation usually achieve returns that are proximate and predictable, but not

necessarily sustainable. March (1991) proposes that exploitation and exploration are

two fundamentally different learning activities between which firms divide their

attention and resources. Furthermore, given the profit-‐seeking nature of firms,

exploitation is often chosen over exploration, much as seen in the case of NZ. Similarly, a

one-‐sided focus on exploitation is said to enhance short-‐term performance, but may

result in ending up in competency trap (Ahuja & Lampert, 2001).

Exploitation and exploration are also said to require fundamentally different

organizational structures and contexts in which different types if innovation can be

expected to emerge (Raisch & Birkinshaw, 2008). Tushman & Smith (2002) describe

incremental innovations (designed to meet existing customers’ needs) as exploitative,

and radical innovations (designed to meet the needs of emergent customers) as

explorative. Levinthal and March conclude that long-‐term survival and success depend

on an organization’s ability to “engage in enough exploitation to ensure the organization’s

current viability and to engage in enough exploration to ensure future viability” (1993:105).


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The above notions are important to understand when assessing a virtual community as

a mechanism to balance exploration and exploitation of R&D activities. In the literature

we find primarily two suggestions of how organizations can balance and synchronize

exploitative and explorative strategies. The first proposes that firms should externalize

either exploitative or explorative activities (Lavie & Rosenkopf, 2006; Rothaermel &

Deeds, 2004). The second argue that it is crucial to carry out the two activities at a

different time and place so they do not plow into one another (Venkatraman, Lee, & Iyer,

2007). Nevertheless, March’s (1991) position is that exploitation and exploration are

two facets of organizational learning that are inseparable, and some scholars argue in

favor of creating loosely coupled organizations in which the explorative units are

strongly buffered against the exploitative units (Levinthal, 1997; Weick, 1976). Echoing

this, other scholars propose that maintaining exploration and exploitation as parallel

activities is not enough to bring value to the firm (Jansen et al., 2009). Furthermore, it

has been stated that it is necessary to integrate these two activities in order to achieve

"unity of effort among the various subsystems in the accomplishment of the organization's task"

(Lawrence and Lorsch, 1967:123).

On the contrary Christensen et al. (1998) postulate that exploratory activities need to be

‘completely separated’ from exploitative units to be able to pursue disruptive innovation.

This notion is further supported by Raisch et al. who emphasize the importance of

"subdivision of tasks into distinct units that tend to develop appropriate…contexts for exploitation

and exploration" (2009: 686). I.e. if boundaries are too permeable between explorative

and exploitative units, constraints imposed by exploitation may “…stifle exploration and

reduce its radius” (Ibid.) Conversely, variations and changes involved by exploration may

destabilize exploitative processes (Raisch et al, 2009).

It seems as though it can be argued whether the two activities should be integrated or

not. We believe that both arguments hold merit in their own right. Separation of

activities is crucial to avoid interference, yet in order to realize the value of novel

combination that emerges in explorative structures, information and knowledge must

somehow be internalized into a process of market captive R&D where

commercialization can take place. As pointed out, we have delimited our paper not to

address how knowledge is to be internalized, appropriated or absorbed and we thereby

pay particular attention to how activities can be separated.


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Obstacles to ambidexterity has been well documented in extant literature, but he

essential challenge resides in dealing with both exploration and exploitation in amore

balanced way, without interference between the two. In Raisch & Birkinshaw (2009) we

learn about two solutions for overcoming obstacles to ambidexterity. The first is a

balance-‐type solution assuming the development of a hybrid of strategies that can

accommodate for both activities simultaneously. The second lies in achieving spatial and

temporal separation of activities through formation of parallel structures. The latter is

often addressed by the theory of punctuated equilibrium that states that organizations

can oscillate between exploitation and exploration in an iterative fashion to avoid

interference by parallel activities, yet allow for both to take place recursively. This,

however, requires an unusual capacity for swift organizational shifts, which is not very

commonplace among larger organizations (Raisch & Birkinshaw (2009). Nevertheless,

the above is of high interest in the light of this thesis, as we infer that a VC set up can be

viewed upon as an explorative arm (add-‐on to the current innovation model at NZ) thus

opening up for such parallel structures of innovative activity. If we recall part II of the

analysis where a set properties of virtual communities was outlined, we emphasized

three key enabling factors of virtual communities for acting as a vehicle for external

knowledge sourcing and search: virtual communities overcome temporal and spatial

barriers, as well as barriers of cognitive-‐, disciplinary-‐ and organizational separation.

Basically, this thesis is exploring the utility of a virtual innovation broker to overcome

obstacles to ambidexterity, and based on the above we suggest that on a conceptual level

there seems to be room for a fit. The solution called for in the literature can be

interpreted as a mechanism for carrying out explorative activities without disturbing

exploitative actives and routines. As such, we find that VIB to be particularly well suited

for the task. In a sense, the VC can be thought of as a second order function that

safeguards the dynamics of the organization by overcoming the contradictory challenge

of stability (exploitation) vs. flexibility (exploration). In the light of our case company, by

means of having access to a network that exists virtually the idea is that NZ can be more

able to balance the countervailing processes of exploitation and exploration and thus

able to capitalize on a more ambidextrous innovation model. Moreover, through a VIB

NZ can potentially rely on virtual and sparse networks during exploration and utilize in-‐

real-‐life teams or tightly bounded groups during exploitation. In addition, the virtual

innovation broker can be hibernated if activities on the virtual platform interfere with


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(steal attention from) the exploitative strategies carried out by the in-‐house R&D

organization, providing a means to oscillate as proposed by Raisch & Birkinshaw (2009).

March (1991) points out that whereas hierarchical structures are more efficient in

exploitation, one should rely on external networks during exploration. We echo March

(1991) in that external networks are key in exploration and move on to suggest that

such networks can be successfully leveraged by means of a virtual innovation broker. In

this respect, given the choice of architectural attributes, a virtual community can

function as a considerably ‘flat’ network. Similarly, following Tushman & O'Reilly (1996),

we learn that while exploitation is better served by bureaucratic structures, exploration

is better supported by organic structures. In this light, the notion of NZ utilizing a virtual

community for exploration receives further support, assuming that structure and

development of a virtual researcher community is more organic than the structure

found at NZ’ R&D organization.

In support of our claim, along the lines of Danzinger & Dumbach (2008), we propose

that ambidextrous organizational attributes indicate that a possible way to create

discontinuous innovation lies in what is referred to as open innovation instruments. A

plethora of open innovation instruments exists (e.g. virtual communities), and such

instruments are said to be suitable for supporting ambidextrous organizational

capabilities (Ibid.). In sum, we infer that a VC indeed holds potential to can act as a tool

to overcome obstacles of ambidexterity.

6.3.3. Ambidextrous innovation A virtual innovation broker (VIB) is a complex socio-‐technical structure, and its

underlying architecture relies on a fundamental understanding of the interaction

between people and technology. In this paper, we go beyond addressing interface-‐ and

communication tools design, and turn to the question of scope. In the case of Novozymes

the VIB is by definition earmarked to act as tool for integrating human agents who are to

some extent cognitively distant from one another, as to produce broader inputs to NZ

R&D organization. In the light of structural holes and ambidexterity theory, we

hypothesize that the scope of distance is a fine balance between being either being too

close to current R&D activities or too distant rendering knowledge inputs redundant.

Thus, the socio-‐technical infrastructure must accommodate for the complex task of

balancing the exploitative and explorative capacity of the platform.


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Below we introduce a model that was outlined in the previous theory section (figure

6.7). In the model, the virtual innovation broker (VIB) is illustrated as a mechanism to

ease the process of concurrent engagement in the two activities of exploration and

exploitation, i.e. widen the scope of engagement along the exploitation-‐exploration

continuum (x-‐axis). The idea is that an organization is unlikely to be able to switch into

forms of full flexibility, and we thereby propose given previously identified enabling

properties of VCs, that a more explorative facet of R&D activities can take place by

means of a VIB.

Figure 6.7: Ambidextrous innovation through a VIB

Source: Own model

By the same token, a VIB can act as a virtual search medium for unguided scientific

discovery, and in our case enable NZ to engage in basic science while keeping its current

applied science-‐based and exploitative oriented innovation model. As pointed out in

part I of the analysis, NZ’ current innovation model has been proved very successful in

the past. It is therefore important that introducing a more explorative scope does not

interfere too much with current activities. Moreover, it is further believed that the

current innovation model provides an important element in realizing the value that

potentially can come to transpire from a successful VC set-‐up. It is believed here, that

such interference will be reduced, given that the nature of interactions in the virtual

world takes place in another dimension (i.e. both temporally and spatially), and can thus

be said to occur separated from present activities of NZ. Finally, we recognize that our

claim is limited to what we know from literature about obstacles to ambidexterity and

our interpretation of the above-‐mentioned VC properties in overcoming those obstacles.


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6.3.4. Conclusion: analysis part III

In part III of the analysis we address the question of whether a virtual community can

make way for a more ambidextrous innovation model. Here we address two important

issues relating to the underlying understanding of external knowledge sourcing: the

notion of optimal scope with regards to cognitive, disciplinary and organizational

distance/separation, and the notion of obstacles to ambidexterity. In this light we

suggest that a virtual innovation broker (VIB), given a set of properties identified in part

II of the analysis, constitute a particularly compelling alternative to facilitate a bridge

between a science-‐based R&D organization such as Novozymes’ and its external

research environment. As such, the VIB can act as a parallel structure in which

explorative activities can take occur without directly interfering with in-‐house R&D

activities.

The optimal scope continuum allows us to understand that while distant sources of

knowledge are of value to an innovation process, there is nonetheless a limit to how

distant and redundant such sources of knowledge can become without rendering the

value obsolete. With the optimal scope continuum we infer that an innovation process

that balances both exploitation and exploration activities holds the potential to provide

inputs of a semi-‐redundant nature, thus opening up for novel combinations to emerge.

Moreover, many scholars have contributed to the discussion of difficulties in balancing

exploitation and exploration. While there are opportunities at either end of the

exploration-‐exploitation continuum, literature and theory highlights that engaging in

both ends of the continuum often renders opportunities at one end superfluous. In this

context we highlight that if formation of groups and interaction across human agents

takes place virtually, barriers of time and space, and barriers of cognitive-‐, disciplinary-‐

and organizational separation can be surmounted. This implies that, in theory, the

explorative domain of R&D can be run as a parallel structure to the exploitative domain,

thereby mitigating issues of that often arise when combining exploitation and

exploration in the same domain (dimension). Ultimately this may lead to more

ambidextrous innovation, assuming that a successful implementation of a virtual

innovation broker can be achieved.


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6.4. Conclusion: Analysis part I, II, II The overall research objective of this thesis has been to explore how a virtual community

can facilitate external knowledge sourcing so as to enhance the innovative capacity of

Novozymes’ R&D organization? In this effort we delimited our paper to take a particular

interest in: (Q1) the current R&D activities at Novozymes; (Q2) a set of enabling

properties of virtual communities for external knowledge sourcing; and (Q3) the

implications of scope with regards to distant search of scientific opportunities and

resource heterogeneity, and ultimately highlighted ways in which a virtual community

platform can overcome obstacles of ambidexterity. Before reaching our final concluding

remarks, we will outline the main contributions from the three parts of the analysis.

Q1: To what extent is the current innovation model at Novozymes conducive for effective

external knowledge sourcing?

We can conclude that Novozymes R&D organization is geared towards producing

market ready products by leveraging strong internal competences centred on

application-‐oriented research. In this light we found that the chain-‐linked model

presents a useful illustration of the current innovation model at NZ. Moreover, we

pointed out that NZ’ model of innovation can be understood as a product of “strong ties”

across the R&D organization and involves a limited set of external collaborations. In

other words, NZ’ current innovation model is successfully exhausting benefits of

localness, high social capital, network closure, exploitation; but is limited in its scope of

explorative activities involving more uncertainty, basic scientific input, distant search

across open networks and raw ideas. While we find evidence that project groups at NZ

are of a cross-‐disciplinary nature, we can conclude that NZ to a certain degree is trapped

in sub-‐optimal routinized exploitative R&D strategies. All R&D activities, ranging from

MB’s to ADU’s as well as external collaborations are limited to cover already targeted

disciplines and industries. The degree of basic scientific research is not adequately

prioritised, despite past examples indicating its vital impact on innovative processes

within R&D of enzyme technology. This is further reflected in the transition of the R&D

organisation, moving from an explorative focus drawing on basic research in the past

towards an exploitative focus, driven by market captive R&D. We conclude that NZ’

innovation model is not particularly conducive for effective external knowledge

sourcing, and suggest that opportunities for frontloading the R&D organisation lie in


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increasing the scope of external networks leveraged with focus on resource

heterogeneity by moving further out along the long tail of R&D.

Q2: How can virtual communities support the facilitation of external knowledge sourcing

for science-‐based firms?

In part II of the analysis we introduced the central phenomenon under investigation in

our thesis, the virtual community (VC). Here we draw on theory and literature to

highlight the rationale for why external knowledge sourcing is of importance so as to

enhance innovative capacity. Following the notion, that bridging structural holes can

result in more novel combinations (radical innovation), we highlight that a special

brokerage mechanism often is needed to create valuable connections across structural

holes. In the context of a virtual community, we expose the concept of the virtual

innovation broker as such a mechanism to support the facilitation of external knowledge

sourcing for science-‐based firms. In view of the context of social interaction in a virtual

world, we understand that virtual communities hold a set of enabling properties, that

are of particular value in the light of our research objective. More specifically, we

highlight the capacity of VCs to overcome barriers of time and space, as well as

cognitive-‐, disciplinary-‐ and organisational separation. Evidence from general trends of

online community life, and results from our online survey, suggest that VCs hold

potential to facilitate an enabling space conducive for external knowledge sourcing.

Virtual communities are becoming an integrated medium for communication and

interaction within the scientific community, and researchers strongly indicate openness

towards the utility of a virtual community for knowledge sharing and collaboration. In

sum, our arguments draw on theory, literature and empirical input, and support our

claim of how a virtual community can facilitate external knowledge sourcing by the

means of a virtual innovation broker. Nevertheless, given the explorative nature as well

as the scope of our paper, we note that in order to confirm with certainly that the value

of a VC is high in the given context, additional success criteria not addressed in this

particular study are necessary to include.

Q3: Can a virtual community make way for an ambidextrous innovation model?

In part III of the analysis the above notion of the virtual innovation broker is taken one

step further and placed under the light of optimal scope of ‘distance’ and ambidextrous


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innovation. While exploitation and exploration activities are important for an innovation

process, there is a limit to the extent to which exploration is of value. Through the

optimal scope continuum we propose that as information moves from being semi-‐

redundant to redundant provided an indication of the outer bounds of the optimal scope.

Obstacles to ambidexterity are addressed through recognizing that exploitation-‐ and

exploration activities require different organisational structures. Where exploitation is

supported through bureaucratic and hierarchical organisational structures; exploration

is supported through organic and flat structures. We infer that by facilitating a VC as a

parallel structure in concurrence with a more exploitation oriented innovation model,

can open up for several benefits. We highlight these by means of our case company,

where we postulate that such an initiative hold potential to enhance the innovative

capacity of NZ, without hampering the internal organisational structure. I.e. in theory,

and provided a number of assumptions regarding opportunities to absorb novel

combinations emerging on the VC platform, a virtual innovation broker can make way

for NZ to surmount obstacles of ambidexterity. Here we point out that due to a set of

enabling properties, VCs can overcome barriers of time and space, and cognitive,

disciplinary and organisational separation -‐ thereby making way for an ambidextrous

innovation model.

In exploring our identified research question we draw upon findings from part I, II and

III of the analysis. We find that, in the context of NZ, a virtual community holds potential

to act as a brokerage function and vehicle for external knowledge sourcing. Specifically,

it can bridge dispersed actors along five dimensions: temporal-‐, geographical-‐, cognitive-‐,

disciplinary-‐ and organisational, in a more effective way than what can be achieved

through an IRL community setting. Not only does it provide NZ with the access to distant

sources of information across previously untargeted disciplines, it also supports

opportunities to gain input from valuable basic oriented research, thereby opening up

for exploration activities transcending the reach of NZ’ current innovation model. In the

light of obstacles to ambidexterity, we have reason to believe that a VIB can play an

important role for balancing more explorative R&D activities along with Novozymes

current exploitative, however remarkably efficient, innovation model. As a result, a VC

holds potential to comprise a cornerstone in developing ambidextrous organizational

capabilities at Novozymes. These are deemed vital given the looming challenges facing

Novozymes in the future of industrial enzyme business.


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Nevertheless, the actual result of VC set-‐up with regards to enhancing NZ’ innovative

capacity remains to be seen after a successful implementation has been carried out. As

of now, we are bound to merely hypothesize that facilitating a VC can indeed enhance

innovative capacity at Novozymes, yet our research provides an optimistic outlook for

why Novozymes should take on an initiative as the one presented in this paper.

7. Discussion of findings and future perspectives Efficient diffusion of knowledge and information is considered the hallmark of a healthy

modern economy (Pyka, 2009). By means of our research we wish to highlight the utility

of ICT in general, and VCs in particular, for making the knowledge economy more

efficient, ultimately resulting in different forms of innovation. The overall message in

this paper is that there is reason to be optimistic about the potential that VCs holds in

facilitating external knowledge sourcing for science-‐based firms. Nevertheless, it

becomes relevant to discuss the implications of our findings, as well as future

perspectives that our research opens up for. Moreover, it is pertinent to ask to what

extent we have contributed to the identified research gap, we initially sat out to address.

Given the embryonic stage of research relating to VCs in the context of innovation, and

the absence of literature regarding research-‐based virtual communities of the kind that

we address in this paper, our case is of a prospective and explorative nature. This has

had both limiting and advantageous bearing on our subsequent findings. We have been

limited to study a hypothetical virtual community set-‐up, thus not been able to provide

empirical evidence with regards to the precise nature and effects of a virtual community

to promote exploration and radical innovation. We are confined to infer only on the

potential opportunities that the phenomenon of VCs holds in the given context, in which

we predominantly rely on inference from theory and literature to reach our concluding

remarks. On the other hand, our approach has allowed us to freely hypothesize and

theorize regarding the use of VCs as to enhance innovation capacity. Moreover, by

combining a pragmatic and theoretical approach, we were able to take a take broad

perspective to our research and use theory and literature in order to shed light on the

phenomenon in question. In this effort we have successfully addressed our pre-‐defined

research gap. Given the lack of studies promoting virtual communities as a tool to be

used by science-‐based firms to broaden their scope and R&D activities, our paper can be


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seen as a preliminary exertion towards highlighting the potential of virtual communities

to facilitate external knowledge sourcing and to overcome obstacles of ambidexterity.

Subsequently, our findings are generalizable on two levels, a pragmatic and a theoretical

level. First, through our case study of Novozymes we find evidence of a predominant

exploitative focus of R&D activities suggesting a lack of exploration. In this light, and

provided that NZ is a firm celebrated for its innovative capacity, our analysis of NZ’

innovation model indicates that (conceivably) other science-‐based R&D intensive firms

may suffer from similar biases. Secondly, our findings are to a certain extent

theoretically generalizable. At the intersection of network-‐, ambidexterity-‐ and

innovation theory and the phenomenon of virtual communities, we present a number of

theoretical claims for why virtual communities hold potential to contribute to

exploration and ambidextrous innovation. An integrated approach of this kind has not

been found in extant literature, and we hold that it provides a nuanced and

comprehensive overview of the mechanisms and dynamics in play regarding the utility

of VCs in the given context. As such, our paper has a positive bearing on the usefulness of

prevailing theoretical constructs in a new setting.

Nonetheless, our paper holds a number of apparent limitations. We only address one

dimension out of many, for understanding how to make use of VCs in the given context.

In order to provide a more comprehensive picture of the utility of VCs for knowledge

sourcing, we envision a number of future research areas that has bearing on our

particular study. We find it important to note, that we recognize that along the line of

most literature regarding opportunities of ICT and virtual communities for knowledge

sourcing and innovation, we too are guided by optimistic suppositions. Thus, in order to

ensure a more nuanced and symmetric debate, more critical perspectives could favour

discourse on the topic of virtual communities in science-‐based innovation. Furthermore,

we are limited to rely on theory on which we base our inferences, thus concrete case

studies presenting the actual effects of VCs should more precisely be able confirm or

reject our claims.

Additionally, in our paper we highlighted that there are strengths and limitations of both

closure and brokerage, but “…while brokerage ... is the source of added value, closure can be

critical to realizing [that] value' (Burt 2001:52). In this light, our paper can be understood


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as an effort to highlight the role of brokerage, i.e. the source of added value that can

come from utilizing virtual communities as a brokerage function en route for remote

and distant actors and knowledge pools. Yet, our study merely touches upon the first

dimension of a two-‐fold inquiry. Correspondingly to Burt’s statement above, following

brokerage comes closure. In that respect it becomes relevant to address how to capture

the value that may transpire. Ensuing research should therefore assess how external

knowledge, captured on the VC, can be effectively internalized as well as commercialized.

It would be of interest to take an intra-‐organizational perspective and analyze how firms

effectively can appropriate, absorb and make use of knowledge emerging from a

successful VC set-‐up. Such research endeavors is favorably carried out in the light of a

retrospective case study, allowing for empirical analysis of knowledge transfer

processes. Exploitation of external knowledge sources is an essential element of a firm’s

innovative capacity, and the notion of absorptive capacity provides a useful concept in

this context with regards to how external knowledge is internalized. Cohen and

Levinthal (1990) state that the absorptive capacity of a firm is the ability to recognize

the value of new information, to integrate it, and to apply it in a commercial context.

Here, current knowledge bases in a firm play an essential role in appropriating external

knowledge; basic skills, experience and the understanding of a particular field provides

a solid foundation by which to evaluate new knowledge. Moreover, absorptive capacity

is said to enhance the ability of a firm to realize the value of the new scientific knowledge

(Cohen and Levinthal, 1990). It is the prior possession of knowledge that supports

creativity through opening up for new associations and linkages between pieces of

knowledge that may not have been obvious before. Thus, the diversity of knowledge

bases internally in the organization is also a crucial role with regards to the assimilation

of novel combinations, i.e. the integration of more radical external knowledge.

Drawing upon the above, future research can be also extended to include development

of strategic recommendations required to successfully implement a VC set-‐up. Our paper

can be considered to provide the underlying rational for undertaking the initiative,

opening up for a more precise plan to be outlined. Here, it would be of interest to take an

operational perspective on the case, where relevant areas to assess would include e.g.:


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platform design-‐ and architecture attributes, platform ownership25 strategies, cost

structures and procedures to ensure user attraction and retention.

Sir Ken Robinson, a well known education researcher, said during a talk at TED26:

“Human resources are much like natural resources, they are buried deep and you have to go

looking for them, they are not just lying around on the surface. And you have to create the

circumstances in which they can show them selves.” By the same token, the architecture of a

VC will to a certain degree define its members and delimit activities that take place.

People tend to cluster into groups as result of interaction opportunities defined by the

places people meet (Pyka, 2009); e.g. the neighborhoods in which they live, the projects

in which they are involved, their workplace as well as the online forums in which they

participate. We infer that just as the architecture of a certain neighborhood is part of

defining the type of people who choose to live there, the architecture of a virtual

community will come to define its members as well as the type of interaction that may

take place in between those members. Through an interview with Peter Kragh, Director

of Front End Innovation at Coloplast27 (founder of innovaiotnbyyou.com), he stated that

a primary recommendation for VC building was to ensure that a learning-‐by-‐doing

principle is employed. He said that one can control the interface design, the

communicative tools and the scope of the focus areas one wish to address etc., but one

cannot control the members. Who is to join only time will tell, and what members will

‘talk’ about is very hard to anticipate. Nonetheless, actions can be taken to influence

what kind of community one is seeking to build. Research drawing upon the above

notions would be highly relevant to take our study one step further.

The phenomenon of virtual communities is becoming an increasingly fascinating target

for social and behavioral science as well as cognitive economics and innovation

literature. One reason for this is, that as a result of advancement of the underlying

computer-‐ and Internet technology supporting the proliferation of virtual communities,

VCs are becoming easier to measure (Burt, 2011). Thus, VCs are to be seen as networks

rich in data available for analysis, which furthermore can come to help improve our 25 Ownership can range from either no ownership where external moderators manage the platform (as seen in the case of Coloplast’s ww.stomainnovation.com) to sponsorship where the firm is a sponsor of the initiative but allow the milieu to grow organically, to full ownership where the firm takes full control and responsibility of implementation, design and content. 26 TED is a nonprofit devoted to Ideas Worth Spreading. It started out (in 1984) as a conference bringing together people from three worlds: Technology, Entertainment, Design. (ted.com) 27 Coloplast is a Danish healthcare firm with focus on products in the ostomy care sector


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understanding of networks in the real world. We echo Burt who urges the entire

academic discourse to “explore virtual worlds as a research site” and “…make virtual

communities legitimate research laboratories to better understand network mechanisms of

innovation…the potential is enormous” (2011:3). In such efforts it becomes important to

establish a clearer link for translating research results between real worlds and virtual

worlds (Ibid.). This further highlights the importance of future research to make use of

retrospective case studies to better concretize and quantify research findings.

Ultimately, we hope that our paper can encourage scholars to take a deeper interest in

virtual communities in the context of innovation.


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“Thanks to the Internet companies that move now can leverage a global pool of talent,

ideas, and innovations that vastly exceeds what they could ever hope to marshal internally”

-‐ USA Today’s editor, Kevin Maney


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8. Bibliography 8.1. Books and Articles Abernathy, W.J. and Clark, K.B. (1985) “Innovation: Mapping the Winds of Creative Destruction.” Research Policy 14(3-‐22) Afuah, A. (2004) Business models: A Strategic Management Approach. McGraw-‐Hill/Irwin, Boston; New York Ahuja, G. (2000) Collaboration networks, structural holes, and innovation: A longitudinal study. Administrative Science Quarterly; 45(3) Sept 2000 Ahuja, G. and C. M. Lampert (2001) Entrepreneurship in large corporations: a longitudinal study of how established firms create breakthrough inventions. Strategic Management Journal 22: 521-‐54 Ancona, D. G., Goodman, P.S., Lawrence, B. S., Tushman. M. L. (2001) Time: A new research lens. Acad. Management Rev. 26 645–663. Anderson, C. (2004) The Long Tail: Why the Future of Business is Selling Less of More. Hyperion, July 11, 2006 Andersen, P.H. (2005) “Relationship marketing and brand involvement of professionals through web-‐enhanced brand communities: The case of Coloplast,” Industrial Marketing Management (34): 39-‐51 Antikainen, M. (2011). Facilitating customer involvement in collaborative online innovation communities, Vtt Publications 760: Tampere, Finland Arora, A., and Gambardella, A. (1994) The changing technology of technological change: General and abstract knowledge and the division of innovative labor. Research Policy, 23: 523-‐532. Balconi, M., Brusoni, S., Orsenigo, L. (2010). In defense of the linear model: An essay. Research Policy 39 Besser, H. (2000) Digital Longevity, in Maxine K. Sitts (ed.) Handbook for Digital Projects: A Management Tool for Preservation and Access Andover Mass: Northeast Document Conservation Center, 2000, pages 155-‐166 Benbya, H. and Belbaly, N. (2011) Successful OSS Project Design and Implementation. Gower Publishing Bian, l., Liu, Y., Agichtein, E. and Zha, H. (2008) Finding the Right Facts in the Crowd: Factoid Question Answering over Social Media. ACM WWW, April 21-‐25, Beijing, China Binz-‐Schar M., (2003) Exploration and Exploitation: Toward a Theory of Knowledge Sharing in Digital Government Projects, Dissertation Nr. 282 at University of St. Gallen, ADAG Copy AG Bitektine A., (2008) Prospective Case Study Design: Qualitative Method for Deductive Theory Testing, Organizational Research Methods 11:160 Bos, N., Zimmerman, A., Olson, J., Yew, J., Yerkie, J., Dahl, E., & Olson, G. (2007) From shared databases to communities of practice: A taxonomy of collaboratories. Journal of Computer Mediated Communication 12(2), article 16.


106

Bourdieu, M. and Wacquant, L. (1992) An Invitation to Reflexive Sociology. Chicago: University of Chicago Press Brandtzæg, P.B, Følstad, A., Obrist, M., Geerts, D., Berg, R. (2010) Innovation in online communities -‐ Towards community-‐centric design, User Centric Media, Springer Link Breshnan T., & Trajtenberg M., (1995) General Purpose Technologies Engines of Growth? Journal of Econometrics 65: 83-‐108, Department of economics, Stanford University Burt, R.

- (1992) Structural Holes: The social structure of competition. Cambridge, Mass.: Harvard University Press

- (1997) The Contingent Value of Social Capital. Johnson Graduate School of Management, Cornell University, Administrative Science Quarterly, 42(2)

- (1997) A note on social capital and network content. Social Networks, 19(1997): 355-‐373 - (2000) The Network Structure of Social Capital. In B. M. Staw and R. I. Sutton: Research in

Organizational Behavior. Amsterdam, London, New York: Elsevier Science JAI, pp. 345-‐423 - (2001) Structural Holes versus Network Closure as Social Capital. In N. Lin, ed. 2001. Social

Capital: Theory and Research. Aldine de Gruyter - (2002) Bridge Decay. Social Networks, 24(2002): 333-‐36 - (2004) Structural Holes and Good Ideas. American Journal of Sociology, 110(2): 349-‐399 - (2005) Brokerage and Closure. Oxford; New York: Oxford University Press - (2011) Structural Holes in Virtual Worlds, Working Paper

Bush, V. (1945) Science The Endless Frontier: Learning from the Past, Designing for the Future, United States Government, Washington D.C. Carroll, M.C. and Stanfield, J.R. (2003) Social capital, Karl Polanyi, and American social and institutional economics. Journal of Economic Issues 37: 397-‐404 Chesbrough, H. (2003) The Era of Open Innovation. Sloan Management Review, 44(3): 35-‐41 Christensen, C. M., Suarez, F. F., and Utterback, J. M. (1998) Strategies for Survival in Fast-‐Changing Industries. Management Science, 44(12): 207-‐220. Coleman, J.S.

- (1988) Social Capital in the Creation of Human Capital. The American Journal of Sociology 94 - (1990) Foundations of Social Theory. Cambridge, MA: Harvard University Press

Cohen, W.M., and Levinthal, D.A. (1990) Absorptive Capacity: A New Perspective on Learning and Innovation. Administrative Science Quarterly 35(1): 128-‐152 Cooper, J.S. and Fava, J. (2006), "Life Cycle Assessment Practitioner Survey: Summary of Results", Journal of Industrial Ecology. 10:12-‐14 Cowan, B. (2005) The Social Life of Coffee: The Emergence of the British Coffee Houses, New Haven: Yale University Press: 89 Cummings, J.N., Butler, B., & Kraut, R. (2002). The Quality of Online Social Relationships. Communications of the ACM, 47(7), 103-‐108. Danzinger, F. and Dumbach, M. (2008) Communities for Innovation as Enablers of Cyclical Ambidexterity. In Danzinger and Dumbach, ed. 2008. SME’s. University of Erlangen-‐Nürnberg Donath J. (2008) Signals in social supernets, Journal of Computer-‐mediated communication 13: 231-‐251


107

Dreyfus, H. (2001) On the Internet. Oxon: Routledge. Egidi M., and Rizzello S., (2003) Cognitive Economics: Foundations and Historical Evolution, Dipartimento di Economia “S. Cognetti de Martiis” Centro di Studi sulla Storia e i Metodi dell’Economia Politica Eisenhardt, K.M. and Martin, J.A. (2000) Dynamic capabilities: What are they? Strategic Management J. 21 1105–1121. Ernst, H. (2003) Patent information for strategic technology management. World Patent Information 25[3], 233-‐242. Fernback, J. (1999) There is a there There: Notes Towards A Definition of Cybercommunity? In S. Jones (Ed.) Doing Internet Research: Critical Issues and Methods for Examining the Net. Thousand Oaks, CA: Sage, 203-‐20. Flavián, C., and Guinalíu, M. (2005) “The influence of virtual communities on distribution strategies in the Internet,” International Journal of Retail & Distribution Management 33(6): 405-‐425. Fleming, L. and Sorensen, O. (2004) “Science as a Map in Technological Search”. Strategic Management Journal 25 (8-‐9), excerpt p. 909-‐911 Freeman, C. and Soete, L. (1997) The Economics of Industrial Innovation. Cambridge, Mass.: MIT Press. Furnas, C.C. (1949). Research in Industry; Its Organisation and Management. D.Van Nostrand Company Inc., New York. Gabbey, M. and Leenders, R. (2001) Social Capital of Organisations. Emerald Group Publishing, 2001 -‐ Business & Economics Gant, J., Ichniowski, C., and Shaw, K. (2002) 'Social capital and organizational change in high-‐involvement and traditional work organizations." Journal of Economics and Management 11: 289-‐328. Glaeser, E.L, Laibson, D., Sacerdote, B. (2002) ‘An economic approach to social capital.' The Economic Journal 112: 437-‐458. Granovetter, M. (1973) The Strength of Weak Ties. American Journal of Sociology 78(6), The University of Chicago Press Guerrie P., and Padoan C., (2007) Modelling ICTs as General Purpose Technologies, Collegium 35 Hagel, J. III, and Armstrong, A.G. (1997) Net Gain: Expanding Markets through Virtual Communities, Harvard Business School Press, Boston, MA Haig, B. (2005). An abductive theory of scientific method. Psychological Methods, 10: 371-‐388 Harmaakorpi, V., Tura, T. and Artima, E. (2006) Balancing regional innovation policy between proximity and distance. Paper presented at the Fifth Proximity Congress, June 28th – 30th, in Bordeaux, France. He L. and Wong, P. (2004) Exploration vs. Exploitation: An Empirical Test of the Ambidexterity Hypothesis, Organizatioanl Sceince, Vol. 15, No. 4, July–August 2004, pp. 481–494 Hill, W.C., Hollan, J.D.. Wroblewski, D., McCandless, T. (1992) "Edit wear and read wear". Proceedings of the SIGCHI conference on Human factors in computing systems


108

Hiltz, S. R. and Wellman, B. (1997) Asynchronous learning networks as a virtual classroom. Communications of the ACM, 40(9): 44-‐49 Holmqvist, M. 2004. Experiential learning processes of exploration and exploitation within and between organizations: An empirical study of product development. Organ. Sci. 15 70–81. Howard, P., Rainie, L., and Jones, S. (2004) Days and nights on the Internet. ITU [International Telecommunication Union] ITU Internet Reports, Labucay Huston, L. and Sakkab, N. (2006) Connect and develop. Inside Procter & Gambles’ new model for innovation. Harvard Business Review. March 2006, 58–66. Jansen, J.J.P., Vera, D., Crossan, M. (2009) Strategic leadership for exploration and exploitation: The moderating role of environmental dynamism. The Leadership Quarterly, Leadership and Organizational Learning. 20(1): 5-‐18 Jovanovic, B & Roussea Peter L. (2005) General Purpose Technologies. In Handbook of Economic Growth. National bureau of economic research, Cambridge Katila, R and Ahuja, G (2002). Something old, something new: A longitudinal study of search behavior and new product introduction. Academy of Management Journal 45(6), 1183-‐1194 Kim, A. J. (2000). Community building on the web: secret strategies for successful online communities. Berkeley: Peachpit Press. Kleinberg, S., Suri, E., Tardos, and Wexler, T. (2008) Strategic network formation with structural holes. ACM Conference on Electronic Commerce, 7(3):1–4 Klevorick, A., Levin, R,. Nelson, R. Winter, S. (1993) “On the sources and significance of inter-‐industry differences in technological opportunities.” Research Policy (24) Kline, S. J. and Rosenberg, N. (1986) "An Overview of Innovation" in Landau, R. and Rosenberg, N.: The Positive Sum Strategy. Washington D. C.: 285 – 298 Knudsen L., and Nielsen B., 2008 Collaborative capability in R&D alliances: exploring the link between organizational and individual level factors, Center for Strategic Management and Globalization, Copenhagen Business School Kvale, S. (1996) Interviews: An introduction to qualitative research interviewing. Sage Publications, Thousand Island Oaks Lakhani, K., (2008) Case Study: Harvard Business School Study of InnoCentive. Harvard Business Review 86(12) Lakhani, K. and Panetta, J. (2007) The Principles of Distributed Innovation. MIT Press Journals. 2007 2(3): 97-‐112 Lavie, D. and L. Rosenkopf (2006) Balancing Exploration and Exploitation in Alliance Formation. Academy of Management Journal, 49:797-‐818. Lawrence, P., and Lorsch, J. (1967) Differentiation and Integration in Complex Organizations. Administrative Science Quarterly 12:1-‐30. Levin-‐Rozalis, M. (2000b). Abduction: A logical criterion for program evolution. Evaluation, the International Journal of Theory, Research and Practice, 6(4), 411-‐428.


109

Levinthal, D. (1997) Adaption on Rugged Landscapes. Management Science. 43(7): 934-‐950 Levinthal, D. and March, J. (1993) The Myopia of Learning, Strategic Management Journal 14:95-‐112 Lin, N., (1999) Building a Network Theory of Social Capital, Connections, Dept. of Sociology, Duke University, Connections 22(1):28-‐51, Lin, N., Cook, K., Burt, R (2001) Social Capital: Theory and Research, Transaction Publishers, New Jersey Lynn, L.H., Reddy, N.M, Aram, J.D. (1994) Linking technology and institutions: the innovation community framework. Research Policy 25 (1996) 91-‐106 March, J.G. (1991) Exploration and exploitation in organizational learning. Organization Science 2(1) McCurdy, D., Spradley, J. and Shandy, D. (2005) Cultural Informants in The Cultural Experience, Waveland Press: chp.3 McDaniel, B.A. (2000) “A survey on Entrepreneurship and Innovation”. University of Northern Colorado McFadyen, M.A. and Cannella, A. (2004) Social Capital and Knowledge Creation: Diminishing returns of the Number and Strength of Exchange Relationships, Academy of Management Journal. 47, (5): 735-‐746. Moeini A., Goldmintz S., Alamgi S. (2006) Lead User Innovation, E-‐Commerce and the Art of High Tech Marketing, Schulich School of Business, York University Moore, G.E., (1965) "Cramming more components onto integrated circuits". Electronics 38 (8) Mulkay, M. (1976) The Mediating Role of the Scientific Elite. Social Studies of Science 6(1976):445-‐70 Muniz, A., and O´Guinn, T.C. (2001) Brand Communities. Journal of consumer research 27: 412-‐432. Nahapiet J, Ghoshal S. (1998) Social capital, intellectual capital and the organizational advantage. Academy of Management Review 23:242-‐266. Nambisan, S. and Sawhney, M. (2007) A Buyer’s Guide to the Innovation Bazaar. Harvard Business Review, June 2007 Narayan, D. (1999) 'Bonds and Bridges: Social Capital and Poverty', World Bank Nelson, J., Kaboolian, Carver K., (2003) The Concord Handbook: How to Build Social Capital Across Communities, UCLA School of Public Policy and Social Research Nooteboom, B.

- (1992) Towards a dynamic theory of transactions. Journal of Evolutionary Economics, 2: 281-‐99

- (1999) Innovation, Learning and Industrial Organisation. Cambridge Journal of Economics, 23(2): 127-‐150.

- (2000) Learning and Innovation in Organizations and Economics. Oxford, Oxford University Press

Nooteboom, B., van Haverbeke, W., Duysters, G., Gilsing, V., and van den Oord, A. (2005) Optimal Cognitive Distance and Absorptive Capacity. Working Paper


110

Obero, P. and Saviott, P. (2010) The impact of cognitive distance on the likelihood of alliance formation: A study in the biotechnology-‐pharmaceutical industry Olson, G. M., and Olson, J. S. (2000) Distance Matters. Human Computer Interaction. 15, 139-‐179. Reprint in Carroll, J. (Ed). Human Computer Interaction in the New Millennium. Addison Wesley O'Reilly, C., and Tushman, M. (2008) "Ambidexterity as a Dynamic Capability: Resolving the Innovator’s Dilemma. Research in Organizational Behavior 28: 185-‐206. Orlikowski, W.J. (1991) Radical and Incremental Innovations in Systems Development: An Empirical Investigation of Case Tools. Center for Information Systems Research, Sloan School of Management, Massachusetts Institute of Technology. Parjanen, S., Hyypiä, M., Oikarinen, T. (2011). Brokerage Functions in Network Level Innovation, Conference Proceedings of OLKC 2011, England Pisano, G.P., and Verganti, R. (2008) Which kind of collaboration is right for you? Harvard Business Review 86(12): 78-‐86 Plant, R (2004) Online Communities, Technology in Society 26: 51–65 Podolny, J.M. and Stuart, T.E. (1995) A role-‐based ecology of technological change. The American Journal of Sociology. 100: 1224-‐1260 Poetz, M., Prügl, R., and Fabsich, C. (2009) ”Systematic Identification of Problem Solvers from Analogous Markets: An Empirical Exploration of the Potential of the Search Method ’Pyramiding’” Polya G., (1941), Heuristic Reasoning and the Theory of Probability. The American Mathematical Monthly 48(7) Portes A., (1998) Social Capital: Its Origins and Applications in Modern Sociology. Annual Review of Sociology. 241998:1-‐24 Portes, A. (2000) The two meanings of social capital. Sociological Forum 15:1-‐12 Preece, J. (2000) Online communities: designing usability, supporting sociability. Chichester: John Wiley & Sons. Preece, J., Nonnecke, B., & Andrews, D. (2004). The top five reasons for lurking: improving community experiences for everyone. Computers in Human Behavior. 20: 201–223. Poole, M. S., A. H. Van de Ven. 1989. Towards a metatheory of innovation process. 49th Annual meeting Acad. Management, Washington, D.C. (August 13–16). Putman, R.D (2000) Bowling Alone: The Collapse and Revival of American Community, Simon & Schuster Pyka A., (2009) Innovation Networks: New Approaches in Modelling and Analysing. Springer-‐Verlag, Berlin Heidelberg Raisch, S. and Birkinshaw, J. (2008) Organizational Ambidexterity: Antecedents, Outcomes, and Moderators. Journal of Management 2008, 34; 375 Raucek, J. (1971) The Challenge of Science in Education. Ayer publishing


111

Rheingold, H. (1993) The Virtual Community: Homesteading on the Electronic Frontier 2. Edition published by the MIT press 2000 Ridings, C., Gefen, D., & Arinze, B. (2002) Some antecedents and effects of trust in virtual communities. Journal of Strategic Information Systems, 11(3-‐4), 271-‐295 Rogers, E. (1995) Diffusion of Innovation, The Free Press Rothaermel, F.T. and Deeds, D.L. (2004) Exploration and exploitation alliances in biotechnology: A system of new product development. Strategic Management Journal, 25 (3): 201-‐221 Saunders, M., Lewis, P., Thornhill, A. (2007) Research Methods for Business Students, Fourth Edition Shan, W., Walker, G. and Kogut, B. (1994) Interfirm Cooperation and Start up Innovation in the Biotechnology Industry, Strategic Management Joumal, 15(5): 387-‐394 Simon, H. A. (2000) Bounded Rationality in Social Science: Today and Tomorrow. Mind & Society 1(1): 25-‐40. Smith, A., (1982) [1759] Theory of Moral Sentiment: 184–5 In: The Glasgow edition of the Works and Correspondence of Adam Smith, vol. I", Oxford University Press Song J.I., (2008) The impact of ICT on space, use and environmental issues, Eco city World Summit 2008 Proceedings Strauss, A. and Corbin, J. (1998) Grounded Theory Methodology: An Overview. In: Denzin, N and Lincoln, Y, ed. 1998. Strategies of Qualitative Inquiry. Thousand Oaks, Sage Publications: 158-‐183 Suarez-‐Villa, L. (1990) “Invention, Inventive Learning and Innovative Capacity.” Behavioral Science, 35(4): 290-‐310. Takahashi, M., Fujimoto, M., & Yamasaki, N. (2002). The active lurker: a new viewpoint for evaluating the influence of an in-‐house. Online Community SIGGROUP Bulletin 23(3): 29–33. Teece, D. J. (1992). Competition, Cooperation, and Innovation: Organizational Arrangements for Regimes of Rapid Technological Progress. Journal of Economic Behaviour and Organization, 18(1) Teece, Pisano and Shuen (1997) Dynamic Capabilities and Strategic Management. Strategic Management Journal (1986-‐1998) Aug 1997, 18(7): 509 Tushman, M., Anderson, P., and O'Reilly, C. (1997) "Technology Cycles, Innovation Streams and Ambidextrous Organizations." In Managing Strategic Innovation and Change, edited by P. Anderson and M. Tushman. New York: Oxford University Press. Tushman, M. and O'Reilly, C. (1996). "Ambidextrous Organizations: Managing Evolutionary and Revolutionary Change." California Management Review 38, no. 4: 8-‐30 Tushman, M. and Smith, W. K. (2002) Organizational Technology. In J. Baum (Ed.), Companion to Organizations: 386-‐414. Malden, MA: Blackwell Van den Bosch, F. A. J., H. W. Volberda, M. de Boer. 1999. Coevolution of firm absorptive capacity and knowledge environment: Organizational forms and combinative capabilities. Organ. Sci. 10 551–568 Varian, H. R (2003) Innovation, Components and Complements. University of California, Berkely Venkatraman, N., Lee, C. H., and Iyer, B. (2007) Strategic ambidexterity and sales growth: A


112

longitudinal test in the software sector. Unpublished Manuscript (earlier version presented at the Academy of Management Meetings, 2005) von Hippel, E.

- (1988) Sources of Innovation. Oxford, New York: Oxford University Press - (1994) Sticky information and locus of problem solving: implication for innovation,

Management of science 40: 429-‐439 Walker, G., Kogut, B., Shan, W. (1997) Social Capital, Structural Holes, and the Formation of an Industry. Organisation Science. 8(2):109 Wallace, W. (1971) The logic of science in sociology. Chicago: Aldine-‐Atherton, 1971. Walliser, B., (2001) “What Cognitive Economics is about" Proceeding of the French School Economie Cognitive. Wasserman, S. and Faust, K. (1994) Social Network Analysis: Method and Application, Cambridge: Cambridge University Press. Weick, K. (1976) Educational organizations as loosely coupled systems, Administrative Science Quarterly, 21: 1-‐9 Wellman, B., and Berkowitz, S. (1988) Social Structures: A Network Approach. Cambridge: Cambridge University Press. Wellman, B., and Haythornthwaite C. (2002) The Internet in everyday life. Oxford: Blackwell Publishers, Fall 2002 Wenger, E., McDermott, R., Snyder, W. (2002) “Cultivating Communities of Practice: A Guide to Managing Knowledge“, Harvard Business School Press, Boston Wilson, J. (2010) Essentials of Business Research: A Guide to Doing Your Research Project: Sage Publications Yin, R. K. (2003). Case study research, design and methods, 3rd ed. Newbury Park: Sage Publications Young, M. L. (2000). Poor Richard’s building online communities: Create a web community for your business, club, association or family. Top Floor Publishing Zhang, J. and Ackerman, M.S. (2005) Searching For Expertise in Social Networks: A simulation of Potential Strategies. ACM GROUP ’05, Nov, 2005, USA


113

8.2. Online sources Biotimes [online] Available at: <http://www.biotimes.com/en/Articles/2011/march/Documents/March_2011_%2020yearswithnovozymesnovamyl_EN.pdf > [Accessed 27 September 2011]

Bullen, P. (2007) Social Capital Factors: Plausible theory about causal relationships [online] Available at: <http://www.mapl.com.au/pdf/SocialCapitalFactors_PlausibleTheoryAboutCausalRelationshipsDraft2a.pdf> [Accessed 30 September 2011] Frost, M. (2008) "The age of Enlightenment" [online] Available at: <http://www.martinfrost.ws/htmlfiles/enlightenment_age.html> [Accessed 7 October 2011] Frost & Sullivan (2009), The U.S. Industrial Enzyme Market, N2C1-‐39, [online] Available at:<http://www.frost.com> [Accessed 8 October 2011] Haskens, T., (2011) Tom Haskens Blog [online] Available at: <http://growchangelearn.blogspot.com/2007/04/vertical-‐and-‐horizontal-‐networks.html> [Accessed 5 October 2011] History of PCR method (1993) A (short) history of PCR [online] Available at: <http://www.scienceisart.com/A_PCR/PCRhistory_2.html> [Accessed 14 October 2011] IOE, Institute of Enzymology [online] Available at: < http://www.enzim.hu/index.php> [Accessed 18 October 2011] Leary P, and Fontahina E. (2007) Communities of Practice and virtual learning communities: benefits, barriers and success factors, eLearning Papers [online] Available at: <http://www.elearningeuropa.info/files/media/media13563.pdf> [Accessed 11 October 2011] McConnell, B., Huba, J. (2006) The 1% Rule: Charting citizen participation [online] Available at: <http://www.churchofthecustomer.com/blog/2006/05/charting_wiki_p.html> [Accessed 7 October 2011] Novozymes Talent Search (2011) Commercial Graduate Program China [online] Available at: <http://www.novozymes.com/en/careers/students/graduate-‐programs/graduate%20program%20china/Pages/default.aspx> [Accessed 30 September 2011] Panetta, J.A. (2008) Distributed Innovation [online] Available at: <http://www.climate-‐tech-‐policy.org/wp/wp-‐content/uploads/2008/Panetta_May08.pdf> [Accessed 13 October 2011] Savvy Auntie (2011) Welcome to Savvy Auntie [online] Available at: <http://www.savvyauntie.com> [Accessed 19 September 2011] Social Capital Research (2011) [online] Available at: <http://www.socialcapitalresearch.com/> [Accessed 21 September 2011] Xinhua H., (2010), The Internet in China [online] Available at: <www.gov.ch: http://www.gov.cn/english/2010-‐06/08/content_1622956_2.htm> [Accessed 21 September 2011]


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9. Appendix The appendix consists of documents, graphs and tables that contain supplementing

information, as well as compilation of interview summaries and meeting notes from our

empirical data.

Appendix: Table of Contents 9. APPENDIX ................................................................................................................................................ 114 APPENDIX 1: INTERVIEW SUMMARY ......................................................................................................................... 115 APPENDIX 2: ONLINE QUESTIONNAIRE SUMMARY ................................................................................................. 146 APPENDIX 3: NOVOZYMES SALES DATA AND GLOBAL ENZYME MARKET ............................................................ 151 APPENDIX 4: ONLINE TRENDS – EMERGING SCIENTIFIC COMMUNITIES ............................................................. 153 APPENDIX 5: ENABLING AND INHIBITING PROPERTIES OF A VIRTUAL COMMUNITY ........................................ 159